IDEAS home Printed from https://ideas.repec.org/f/c/ple536.html
   My authors  Follow this author

Miguel Lejeune

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Pierre Bonami & Miguel A. Lejeune, 2009. "An Exact Solution Approach for Integer Constrained Portfolio Optimization Problems Under Stochastic Constraints," Post-Print hal-00421756, HAL.

    Cited by:

    1. Eduardo Bered Fernandes Vieira & Tiago Pascoal Filomena, 2020. "Liquidity Constraints for Portfolio Selection Based on Financial Volume," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 1055-1077, December.
    2. Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.
    3. Stefan Gerhold & Paul Kruhner, 2017. "Dynamic trading under integer constraints," Papers 1708.07661, arXiv.org.
    4. Vanita Garg & Kusum Deep, 2019. "Portfolio optimization using Laplacian biogeography based optimization," OPSEARCH, Springer;Operational Research Society of India, vol. 56(4), pages 1117-1141, December.
    5. Alexander Vinel & Pavlo Krokhmal, 2014. "On Valid Inequalities for Mixed Integer p-Order Cone Programming," Journal of Optimization Theory and Applications, Springer, vol. 160(2), pages 439-456, February.
    6. Martin Branda & Max Bucher & Michal Červinka & Alexandra Schwartz, 2018. "Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization," Computational Optimization and Applications, Springer, vol. 70(2), pages 503-530, June.
    7. Zhou, Zhongbao & Jin, Qianying & Xiao, Helu & Wu, Qian & Liu, Wenbin, 2018. "Estimation of cardinality constrained portfolio efficiency via segmented DEA," Omega, Elsevier, vol. 76(C), pages 28-37.
    8. Massol, Olivier & Banal-Estañol, Albert, 2014. "Export diversification through resource-based industrialization: The case of natural gas," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1067-1082.
    9. Alper Atamtürk & Hyemin Jeon, 2019. "Lifted polymatroid inequalities for mean-risk optimization with indicator variables," Journal of Global Optimization, Springer, vol. 73(4), pages 677-699, April.
    10. Ran Ji & Miguel A. Lejeune, 2021. "Data-Driven Optimization of Reward-Risk Ratio Measures," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1120-1137, July.
    11. Shijie Liu & Andrew Adams & Boulis M. Ibrahim, 2013. "Effects of Tax on Investment Portfolios and Financial Markets Under Mixed Integer Stochastic Programming," CFI Discussion Papers 1304, Centre for Finance and Investment, Heriot Watt University.
    12. Hsia, Yong & Wu, Baiyi & Li, Duan, 2014. "New reformulations for probabilistically constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 233(3), pages 550-556.
    13. Kay Giesecke & Baeho Kim & Jack Kim & Gerry Tsoukalas, 2014. "Optimal Credit Swap Portfolios," Management Science, INFORMS, vol. 60(9), pages 2291-2307, September.
    14. Murray, Chase C. & Talukdar, Debabrata & Gosavi, Abhijit, 2010. "Joint Optimization of Product Price, Display Orientation and Shelf-Space Allocation in Retail Category Management," Journal of Retailing, Elsevier, vol. 86(2), pages 125-136.
    15. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    16. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.
    17. Ralph Steuer & Markus Hirschberger & Kalyanmoy Deb, 2016. "Extracting from the relaxed for large-scale semi-continuous variable nondominated frontiers," Journal of Global Optimization, Springer, vol. 64(1), pages 33-48, January.
    18. X. Cui & X. Zheng & S. Zhu & X. Sun, 2013. "Convex relaxations and MIQCQP reformulations for a class of cardinality-constrained portfolio selection problems," Journal of Global Optimization, Springer, vol. 56(4), pages 1409-1423, August.
    19. Tiago P. Filomena & Miguel A. Lejeune, 2014. "Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 308-329, April.
    20. Zheng, Xiaojin & Sun, Xiaoling & Li, Duan & Cui, Xueting, 2012. "Lagrangian decomposition and mixed-integer quadratic programming reformulations for probabilistically constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 221(1), pages 38-48.
    21. Xiaojin Zheng & Xiaoling Sun & Duan Li & Jie Sun, 2014. "Successive convex approximations to cardinality-constrained convex programs: a piecewise-linear DC approach," Computational Optimization and Applications, Springer, vol. 59(1), pages 379-397, October.
    22. Moarefdoost, M. Mohsen & Lamadrid, Alberto J. & Zuluaga, Luis F., 2016. "A robust model for the ramp-constrained economic dispatch problem with uncertain renewable energy," Energy Economics, Elsevier, vol. 56(C), pages 310-325.
    23. Ran Ji & Miguel A. Lejeune & Srinivas Y. Prasad, 2017. "Properties, formulations, and algorithms for portfolio optimization using Mean-Gini criteria," Annals of Operations Research, Springer, vol. 248(1), pages 305-343, January.
    24. Miguel A. Lejeune, 2012. "Game Theoretical Approach for Reliable Enhanced Indexation," Decision Analysis, INFORMS, vol. 9(2), pages 146-155, June.
    25. Kyle Steinhauer & Takahisa Fukadai & Sho Yoshida, 2020. "Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation," Papers 2009.08412, arXiv.org.
    26. Liu, Kanglin & Li, Qiaofeng & Zhang, Zhi-Hai, 2019. "Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 79-101.
    27. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2011. "Heuristic algorithms for the cardinality constrained efficient frontier," European Journal of Operational Research, Elsevier, vol. 213(3), pages 538-550, September.
    28. Stefan Gerhold & Paul Krühner, 2018. "Dynamic trading under integer constraints," Finance and Stochastics, Springer, vol. 22(4), pages 919-957, October.
    29. Zhe Liu & Shurong Li, 2022. "A numerical method for interval multi-objective mixed-integer optimal control problems based on quantum heuristic algorithm," Annals of Operations Research, Springer, vol. 311(2), pages 853-898, April.
    30. Jongbin Jung & Seongmoon Kim, 2017. "Developing a dynamic portfolio selection model with a self-adjusted rebalancing method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 766-779, July.
    31. Miten Mistry & Dimitrios Letsios & Gerhard Krennrich & Robert M. Lee & Ruth Misener, 2021. "Mixed-Integer Convex Nonlinear Optimization with Gradient-Boosted Trees Embedded," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1103-1119, July.
    32. Liu, Kanglin & Zhang, Zhi-Hai, 2018. "Capacitated disassembly scheduling under stochastic yield and demand," European Journal of Operational Research, Elsevier, vol. 269(1), pages 244-257.
    33. Gili Rosenberg & Poya Haghnegahdar & Phil Goddard & Peter Carr & Kesheng Wu & Marcos L'opez de Prado, 2015. "Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer," Papers 1508.06182, arXiv.org, revised Aug 2016.
    34. Panos Xidonas & Christis Hassapis & George Mavrotas & Christos Staikouras & Constantin Zopounidis, 2018. "Multiobjective portfolio optimization: bridging mathematical theory with asset management practice," Annals of Operations Research, Springer, vol. 267(1), pages 585-606, August.
    35. Vedat Bayram & Hande Yaman, 2018. "Shelter Location and Evacuation Route Assignment Under Uncertainty: A Benders Decomposition Approach," Transportation Science, INFORMS, vol. 52(2), pages 416-436, March.
    36. Dorsaf Cherif & Meriam El Mansour & Emmanuel Lepinette, 2023. "A short note on super-hedging an arbitrary number of European options with integer-valued strategies," Papers 2311.08871, arXiv.org.
    37. Carina Moreira Costa & Dennis Kreber & Martin Schmidt, 2022. "An Alternating Method for Cardinality-Constrained Optimization: A Computational Study for the Best Subset Selection and Sparse Portfolio Problems," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 2968-2988, November.
    38. Miguel A. Lejeune & François Margot, 2016. "Solving Chance-Constrained Optimization Problems with Stochastic Quadratic Inequalities," Operations Research, INFORMS, vol. 64(4), pages 939-957, August.
    39. Patrizia Beraldi & Maria Bruni & Antonio Violi, 2012. "Capital rationing problems under uncertainty and risk," Computational Optimization and Applications, Springer, vol. 51(3), pages 1375-1396, April.
    40. Zhang, Zhi-Hai & Unnikrishnan, Avinash, 2016. "A coordinated location-inventory problem in closed-loop supply chain," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 127-148.
    41. Fereshteh Vaezi & Seyed Jafar Sadjadi & Ahmad Makui, 2019. "A portfolio selection model based on the knapsack problem under uncertainty," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-19, May.
    42. Philipp Baumann & Norbert Trautmann, 2013. "Portfolio-optimization models for small investors," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 345-356, June.
    43. Xueting Cui & Xiaoling Sun & Shushang Zhu & Rujun Jiang & Duan Li, 2018. "Portfolio Optimization with Nonparametric Value at Risk: A Block Coordinate Descent Method," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 454-471, August.
    44. Chien-Ming Chen & Joe Zhu, 2011. "Efficient Resource Allocation via Efficiency Bootstraps: An Application to R&D Project Budgeting," Operations Research, INFORMS, vol. 59(3), pages 729-741, June.
    45. Todor Stoilov & Krasimira Stoilova & Miroslav Vladimirov, 2021. "Explicit Value at Risk Goal Function in Bi-Level Portfolio Problem for Financial Sustainability," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    46. Dimitris Bertsimas & Ryan Cory-Wright, 2022. "A Scalable Algorithm for Sparse Portfolio Selection," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1489-1511, May.
    47. Mike G. Tsionas & Dionisis Philippas & Constantin Zopounidis, 2023. "Exploring Uncertainty, Sensitivity and Robust Solutions in Mathematical Programming Through Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 205-227, June.
    48. Jianjun Gao & Duan Li, 2013. "Optimal Cardinality Constrained Portfolio Selection," Operations Research, INFORMS, vol. 61(3), pages 745-761, June.
    49. Amir Ahmadi-Javid & Pooya Hoseinpour, 2022. "Convexification of Queueing Formulas by Mixed-Integer Second-Order Cone Programming: An Application to a Discrete Location Problem with Congestion," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2621-2633, September.

Articles

  1. Ran Ji & Miguel A. Lejeune, 2021. "Data-driven distributionally robust chance-constrained optimization with Wasserstein metric," Journal of Global Optimization, Springer, vol. 79(4), pages 779-811, April.

    Cited by:

    1. Zheng, Yi & Wang, Jiawei & You, Shi & Li, Ximei & Bindner, Henrik W. & Münster, Marie, 2023. "Data-driven scheme for optimal day-ahead operation of a wind/hydrogen system under multiple uncertainties," Applied Energy, Elsevier, vol. 329(C).
    2. Nilay Noyan & Gábor Rudolf & Miguel Lejeune, 2022. "Distributionally Robust Optimization Under a Decision-Dependent Ambiguity Set with Applications to Machine Scheduling and Humanitarian Logistics," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 729-751, March.
    3. van der Laan, Niels & Teunter, Ruud H. & Romeijnders, Ward & Kilic, Onur A., 2022. "The data-driven newsvendor problem: Achieving on-target service-levels using distributionally robust chance-constrained optimization," International Journal of Production Economics, Elsevier, vol. 249(C).
    4. Yue Zhao & Zhi Chen & Zhenzhen Zhang, 2023. "Distributionally Robust Chance-Constrained p -Hub Center Problem," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1361-1382, November.
    5. Zhai, Junyi & Wang, Sheng & Guo, Lei & Jiang, Yuning & Kang, Zhongjian & Jones, Colin N., 2022. "Data-driven distributionally robust joint chance-constrained energy management for multi-energy microgrid," Applied Energy, Elsevier, vol. 326(C).

  2. Dmitry Anokhin & Payman Dehghanian & Miguel A. Lejeune & Jinshun Su, 2021. "Mobility‐As‐A‐Service for Resilience Delivery in Power Distribution Systems," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2492-2521, August.

    Cited by:

    1. Magoua, Joseph Jonathan & Li, Nan, 2023. "The human factor in the disaster resilience modeling of critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    2. Wang, Hongping & Fang, Yi-Ping & Zio, Enrico, 2022. "Resilience-oriented optimal post-disruption reconfiguration for coupled traffic-power systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Tsan‐Ming Choi & Subodha Kumar & Xiaohang Yue & Hau‐Ling Chan, 2022. "Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 9-31, January.
    4. Dong, Yuchen & Zheng, Weibo & Cao, Xiaoyu & Sun, Xunhang & He, Zhengwen, 2023. "Co-planning of hydrogen-based microgrids and fuel-cell bus operation centers under low-carbon and resilience considerations," Applied Energy, Elsevier, vol. 336(C).

  3. So Yeon Chun & Miguel A. Lejeune, 2020. "Risk-Based Loan Pricing: Portfolio Optimization Approach with Marginal Risk Contribution," Management Science, INFORMS, vol. 66(8), pages 3735-3753, August.

    Cited by:

    1. Lei Lu & Jianxing Wei & Weixing Wu & Yi Zhou, 2023. "Pricing strategies in BigTech lending: Evidence from China," Financial Management, Financial Management Association International, vol. 52(2), pages 333-374, June.
    2. Iryna Yanenkova & Yuliia Nehoda & Svetlana Drobyazko & Andrii Zavhorodnii & Lyudmyla Berezovska, 2021. "Modeling of Bank Credit Risk Management Using the Cost Risk Model," JRFM, MDPI, vol. 14(5), pages 1-15, May.
    3. Bernd Engelmann & Ha Pham, 2020. "A Raroc Valuation Scheme for Loans and Its Application in Loan Origination," Risks, MDPI, vol. 8(2), pages 1-20, June.
    4. Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.
    5. Jun Wang & Qian Zhang & Pengwen Hou, 2022. "Implications of credit default and yield uncertainty on supply chain’s equilibrium financial strategy," Annals of Operations Research, Springer, vol. 315(1), pages 507-533, August.

  4. Miguel A. Lejeune & John Turner, 2019. "Planning Online Advertising Using Gini Indices," Operations Research, INFORMS, vol. 67(5), pages 1222-1245, September.

    Cited by:

    1. Abhijeet Ghoshal & Radha Mookerjee & Zhen Sun, 2023. "Serving two masters? Optimizing mobile ad contracts with heterogeneous advertisers," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 618-636, February.

  5. Azrah Anparasan & Miguel Lejeune, 2019. "Resource deployment and donation allocation for epidemic outbreaks," Annals of Operations Research, Springer, vol. 283(1), pages 9-32, December.

    Cited by:

    1. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    2. Xiaoyan Xu & Suresh P. Sethi & Sai‐Ho Chung & Tsan‐Ming Choi, 2023. "Reforming global supply chain management under pandemics: The GREAT‐3Rs framework," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 524-546, February.
    3. Biswas, Debajyoti & Alfandari, Laurent, 2022. "Designing an optimal sequence of non‐pharmaceutical interventions for controlling COVID-19," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1372-1391.
    4. Yashoda Devi & Sabyasachi Patra & Surya Prakash Singh, 2022. "A location-allocation model for influenza pandemic outbreaks: A case study in India," Operations Management Research, Springer, vol. 15(1), pages 487-502, June.
    5. Paula Camargo Fiorini & Charbel Jose Chiappetta Jabbour & Ana Beatriz Lopes de Sousa Jabbour & Gary Ramsden, 2022. "The human side of humanitarian supply chains: a research agenda and systematization framework," Annals of Operations Research, Springer, vol. 319(1), pages 911-936, December.
    6. Mohammadi, Mehrdad & Dehghan, Milad & Pirayesh, Amir & Dolgui, Alexandre, 2022. "Bi‐objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID‐19 pandemic," Omega, Elsevier, vol. 113(C).
    7. Linus Nyiwul, 2021. "Epidemic Control and Resource Allocation: Approaches and Implications for the Management of COVID-19," Studies in Microeconomics, , vol. 9(2), pages 283-305, December.
    8. Kumar Mangla, Sachin & Chauhan, Ankur & Kundu, Tanmoy & Mardani, Abbas, 2023. "Emergency order allocation of e-medical supplies due to the disruptive events of the healthcare crisis," Journal of Business Research, Elsevier, vol. 155(PA).
    9. Salarpour, Mojtaba & Nagurney, Anna, 2021. "A multicountry, multicommodity stochastic game theory network model of competition for medical supplies inspired by the Covid-19 pandemic," International Journal of Production Economics, Elsevier, vol. 236(C).
    10. Manjul Gupta & Amin Shoja & Patrick Mikalef, 2022. "Toward the understanding of national culture in the success of non‐pharmaceutical technological interventions in mitigating COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1433-1450, December.
    11. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    12. Sameer Kumar & Chong Xu & Nidhi Ghildayal & Charu Chandra & Muer Yang, 2022. "Social media effectiveness as a humanitarian response to mitigate influenza epidemic and COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 823-851, December.
    13. Bakker, Hannah & Bindewald, Viktor & Dunke, Fabian & Nickel, Stefan, 2023. "Logistics for diagnostic testing: An adaptive decision-support framework," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1120-1133.
    14. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    15. Peiyu Zhang & Yankui Liu & Guoqing Yang & Guoqing Zhang, 2022. "A multi-objective distributionally robust model for sustainable last mile relief network design problem," Annals of Operations Research, Springer, vol. 309(2), pages 689-730, February.

  6. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.

    Cited by:

    1. Janostik, Radek & Konecny, Jan & Krajča, Petr, 2020. "Interface between Logical Analysis of Data and Formal Concept Analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 792-800.

  7. Miguel A. Lejeune & Francois Margot, 2018. "Aeromedical Battlefield Evacuation Under Endogenous Uncertainty in Casualty Delivery Times," Management Science, INFORMS, vol. 64(12), pages 5481-5496, December.

    Cited by:

    1. Phillip R. Jenkins & Matthew J. Robbins & Brian J. Lunday, 2021. "Approximate Dynamic Programming for Military Medical Evacuation Dispatching Policies," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 2-26, January.
    2. Jenkins, Phillip R. & Lunday, Brian J. & Robbins, Matthew J., 2020. "Robust, multi-objective optimization for the military medical evacuation location-allocation problem," Omega, Elsevier, vol. 97(C).
    3. Alizadeh, Morteza & Amiri-Aref, Mehdi & Mustafee, Navonil & Matilal, Sumohon, 2019. "A robust stochastic Casualty Collection Points location problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 965-983.
    4. Robbins, Matthew J. & Jenkins, Phillip R. & Bastian, Nathaniel D. & Lunday, Brian J., 2020. "Approximate dynamic programming for the aeromedical evacuation dispatching problem: Value function approximation utilizing multiple level aggregation," Omega, Elsevier, vol. 91(C).

  8. Miguel A. Lejeune & Janne Kettunen, 2018. "A fractional stochastic integer programming problem for reliability-to-stability ratio in forest harvesting," Computational Management Science, Springer, vol. 15(3), pages 583-597, October.

    Cited by:

    1. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.

  9. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.

    Cited by:

    1. Al Janabi, Mazin A.M. & Arreola Hernandez, Jose & Berger, Theo & Nguyen, Duc Khuong, 2017. "Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1121-1131.
    2. Sebastian Jaimungal & Silvana M. Pesenti & Yuri F. Saporito & Rodrigo S. Targino, 2023. "Risk Budgeting Allocation for Dynamic Risk Measures," Papers 2305.11319, arXiv.org, revised Mar 2024.
    3. Giorgio Costa & Roy Kwon, 2020. "A robust framework for risk parity portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 447-466, September.
    4. Singh, Vikas Vikram & Lisser, Abdel & Arora, Monika, 2021. "An equivalent mathematical program for games with random constraints," Statistics & Probability Letters, Elsevier, vol. 174(C).
    5. Anis, Hassan T. & Kwon, Roy H., 2022. "Cardinality-constrained risk parity portfolios," European Journal of Operational Research, Elsevier, vol. 302(1), pages 392-402.
    6. Hoang Nam Nguyen & Abdel Lisser & Vikas Vikram Singh, 2022. "Random Games Under Elliptically Distributed Dependent Joint Chance Constraints," Journal of Optimization Theory and Applications, Springer, vol. 195(1), pages 249-264, October.

  10. Azrah A. Anparasan & Miguel A. Lejeune, 2018. "Data laboratory for supply chain response models during epidemic outbreaks," Annals of Operations Research, Springer, vol. 270(1), pages 53-64, November.

    Cited by:

    1. Juliano Marçal Lopes & Coralys Colon Morales & Michelle Alvarado & Vidal Augusto Z. C. Melo & Leonardo Batista Paiva & Eduardo Mario Dias & Panos M. Pardalos, 2022. "Optimization methods for large-scale vaccine supply chains: a rapid review," Annals of Operations Research, Springer, vol. 316(1), pages 699-721, September.
    2. Narayan Prasad Nagendra & Gopalakrishnan Narayanamurthy & Roger Moser, 2022. "Management of humanitarian relief operations using satellite big data analytics: the case of Kerala floods," Annals of Operations Research, Springer, vol. 319(1), pages 885-910, December.
    3. Hammami, Ramzi & Salman, Sinan & Khouja, Moutaz & Nouira, Imen & Alaswad, Suzan, 2023. "Government strategies to secure the supply of medical products in pandemic times," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1364-1387.
    4. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    5. Xuanlong Qin & Danish Iqbal Godil & Muhammad Kamran Khan & Salman Sarwat & Sadaf Alam & Laeeq Janjua, 2022. "Investigating the effects of COVID-19 and public health expenditure on global supply chain operations: an empirical study," Operations Management Research, Springer, vol. 15(1), pages 195-207, June.
    6. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    7. Xiaoyan Xu & Suresh P. Sethi & Sai‐Ho Chung & Tsan‐Ming Choi, 2023. "Reforming global supply chain management under pandemics: The GREAT‐3Rs framework," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 524-546, February.
    8. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    9. Salarpour, Mojtaba & Nagurney, Anna, 2021. "A multicountry, multicommodity stochastic game theory network model of competition for medical supplies inspired by the Covid-19 pandemic," International Journal of Production Economics, Elsevier, vol. 236(C).
    10. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    11. Manupati, Vijaya Kumar & Schoenherr, Tobias & Subramanian, Nachiappan & Ramkumar, M. & Soni, Bhanushree & Panigrahi, Suraj, 2021. "A multi-echelon dynamic cold chain for managing vaccine distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    12. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2023. "Design of control strategies to help prevent the spread of COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 219-238.

  11. Miguel A. Lejeune & Janne Kettunen, 2017. "Managing Reliability and Stability Risks in Forest Harvesting," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 620-638, October.

    Cited by:

    1. Song, Malin & Xie, Qianjiao & Tan, Kim Hua & Wang, Jianlin, 2020. "A fair distribution and transfer mechanism of forest tourism benefits in China," China Economic Review, Elsevier, vol. 63(C).
    2. Ran Ji & Miguel A. Lejeune, 2021. "Data-Driven Optimization of Reward-Risk Ratio Measures," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1120-1137, July.
    3. Miguel A. Lejeune & Janne Kettunen, 2018. "A fractional stochastic integer programming problem for reliability-to-stability ratio in forest harvesting," Computational Management Science, Springer, vol. 15(3), pages 583-597, October.

  12. Ran Ji & Miguel A. Lejeune & Srinivas Y. Prasad, 2017. "Properties, formulations, and algorithms for portfolio optimization using Mean-Gini criteria," Annals of Operations Research, Springer, vol. 248(1), pages 305-343, January.

    Cited by:

    1. Ruchika Sehgal & Aparna Mehra, 2019. "Enhanced indexing using weighted conditional value at risk," Annals of Operations Research, Springer, vol. 280(1), pages 211-240, September.
    2. Zhenlong Jiang & Ran Ji & Kuo-Chu Chang, 2020. "A Machine Learning Integrated Portfolio Rebalance Framework with Risk-Aversion Adjustment," JRFM, MDPI, vol. 13(7), pages 1-20, July.
    3. Sally G. Arcidiacono & Damiano Rossello, 2022. "A hybrid approach to the discrepancy in financial performance’s robustness," Operational Research, Springer, vol. 22(5), pages 5441-5476, November.

  13. Lejeune, Miguel A. & Shen, Siqian, 2016. "Multi-objective probabilistically constrained programs with variable risk: Models for multi-portfolio financial optimization," European Journal of Operational Research, Elsevier, vol. 252(2), pages 522-539.

    Cited by:

    1. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    2. Horng, Shih-Cheng & Lin, Shieh-Shing, 2019. "Bat algorithm assisted by ordinal optimization for solving discrete probabilistic bicriteria optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 166(C), pages 346-364.
    3. Ki Taek Park & Hyejeong Yang & So Young Sohn, 2022. "Recommendation of investment portfolio for peer-to-peer lending with additional consideration of bidding period," Annals of Operations Research, Springer, vol. 315(2), pages 1083-1105, August.
    4. Marla, Lavanya & Rikun, Alexander & Stauffer, Gautier & Pratsini, Eleni, 2020. "Robust modeling and planning: Insights from three industrial applications," Operations Research Perspectives, Elsevier, vol. 7(C).
    5. Nilay Noyan & Gábor Rudolf & Miguel Lejeune, 2022. "Distributionally Robust Optimization Under a Decision-Dependent Ambiguity Set with Applications to Machine Scheduling and Humanitarian Logistics," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 729-751, March.
    6. Miguel A. Lejeune & Janne Kettunen, 2018. "A fractional stochastic integer programming problem for reliability-to-stability ratio in forest harvesting," Computational Management Science, Springer, vol. 15(3), pages 583-597, October.
    7. Yiling Zhang & Jin Dong, 2022. "Building Load Control Using Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty and the Risk-Adjustable Variants," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1531-1547, May.
    8. Balbás, Alejandro & Balbás, Beatriz & Balbás, Raquel, 2017. "Differential equations connecting VaR and CVaR," INDEM - Working Paper Business Economic Series 24017, Instituto para el Desarrollo Empresarial (INDEM).
    9. Zheng, Xiaojin & Wu, Baiyi & Cui, Xueting, 2017. "Cell-and-bound algorithm for chance constrained programs with discrete distributions," European Journal of Operational Research, Elsevier, vol. 260(2), pages 421-431.

  14. Miguel A. Lejeune & François Margot, 2016. "Solving Chance-Constrained Optimization Problems with Stochastic Quadratic Inequalities," Operations Research, INFORMS, vol. 64(4), pages 939-957, August.

    Cited by:

    1. Gong, Zaiwu & Guo, Weiwei & Herrera-Viedma, Enrique & Gong, Zejun & Wei, Guo, 2020. "Consistency and consensus modeling of linear uncertain preference relations," European Journal of Operational Research, Elsevier, vol. 283(1), pages 290-307.
    2. Liu, Bingbing & Guo, Xiaolong & Yu, Yugang & Zhou, Qiang, 2019. "Minimizing the total completion time of an urban delivery problem with uncertain assembly time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 132(C), pages 163-182.
    3. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    4. Xiaodi Bai & Jie Sun & Xiaojin Zheng, 2021. "An Augmented Lagrangian Decomposition Method for Chance-Constrained Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1056-1069, July.
    5. Xiao Liu & Simge Küçükyavuz, 2018. "A polyhedral study of the static probabilistic lot-sizing problem," Annals of Operations Research, Springer, vol. 261(1), pages 233-254, February.
    6. D. K. Mohanty & Avik Pradhan & M. P. Biswal, 2020. "Chance constrained programming with some non-normal continuous random variables," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1281-1298, December.
    7. Roya Karimi & Jianqiang Cheng & Miguel A. Lejeune, 2021. "A Framework for Solving Chance-Constrained Linear Matrix Inequality Programs," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1015-1036, July.
    8. Zheng, Xiaojin & Wu, Baiyi & Cui, Xueting, 2017. "Cell-and-bound algorithm for chance constrained programs with discrete distributions," European Journal of Operational Research, Elsevier, vol. 260(2), pages 421-431.
    9. Lukáš Adam & Martin Branda, 2016. "Nonlinear Chance Constrained Problems: Optimality Conditions, Regularization and Solvers," Journal of Optimization Theory and Applications, Springer, vol. 170(2), pages 419-436, August.
    10. Emily Speakman & Jon Lee, 2017. "Quantifying Double McCormick," Mathematics of Operations Research, INFORMS, vol. 42(4), pages 1230-1253, November.
    11. Rashed Khanjani-Shiraz & Salman Khodayifar & Panos M. Pardalos, 2021. "Copula theory approach to stochastic geometric programming," Journal of Global Optimization, Springer, vol. 81(2), pages 435-468, October.

  15. Xing Hong & Miguel A. Lejeune & Nilay Noyan, 2015. "Stochastic network design for disaster preparedness," IISE Transactions, Taylor & Francis Journals, vol. 47(4), pages 329-357, April.

    Cited by:

    1. Jyotirmoy Dalal & Halit Üster, 2021. "Robust Emergency Relief Supply Planning for Foreseen Disasters Under Evacuation-Side Uncertainty," Transportation Science, INFORMS, vol. 55(3), pages 791-813, May.
    2. Aigner, Kevin-Martin & Clarner, Jan-Patrick & Liers, Frauke & Martin, Alexander, 2022. "Robust approximation of chance constrained DC optimal power flow under decision-dependent uncertainty," European Journal of Operational Research, Elsevier, vol. 301(1), pages 318-333.
    3. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    4. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    5. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    6. Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.
    7. Akbarpour, Mina & Ali Torabi, S. & Ghavamifar, Ali, 2020. "Designing an integrated pharmaceutical relief chain network under demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    8. Nilay Noyan & Gökçe Kahvecioğlu, 2018. "Stochastic last mile relief network design with resource reallocation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 187-231, January.
    9. Renata Turkeš & Kenneth Sörensen & Daniel Palhazi Cuervo, 2021. "A matheuristic for the stochastic facility location problem," Journal of Heuristics, Springer, vol. 27(4), pages 649-694, August.
    10. Muhammad Salman Habib & Biswajit Sarkar, 2017. "An Integrated Location-Allocation Model for Temporary Disaster Debris Management under an Uncertain Environment," Sustainability, MDPI, vol. 9(5), pages 1-26, April.
    11. Ghasemi, Peiman & Khalili-Damghani, Kaveh & Hafezalkotob, Ashkan & Raissi, Sadigh, 2020. "Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake)," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    12. Miguel A. Lejeune & Francois Margot, 2018. "Aeromedical Battlefield Evacuation Under Endogenous Uncertainty in Casualty Delivery Times," Management Science, INFORMS, vol. 64(12), pages 5481-5496, December.
    13. Huang, Hai-Jun & Xia, Tian & Tian, Qiong & Liu, Tian-Liang & Wang, Chenlan & Li, Daqing, 2020. "Transportation issues in developing China's urban agglomerations," Transport Policy, Elsevier, vol. 85(C), pages 1-22.
    14. Tanzid Hasnain & Irem Sengul Orgut & Julie Simmons Ivy, 2021. "Elicitation of Preference among Multiple Criteria in Food Distribution by Food Banks," Production and Operations Management, Production and Operations Management Society, vol. 30(12), pages 4475-4500, December.
    15. Balcik, Burcu & Yanıkoğlu, İhsan, 2020. "A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty," European Journal of Operational Research, Elsevier, vol. 282(1), pages 40-57.
    16. Rezapour, Shabnam & Farahani, Reza Zanjirani & Morshedlou, Nazanin, 2021. "Impact of timing in post-warning prepositioning decisions on performance measures of disaster management: A real-life application," European Journal of Operational Research, Elsevier, vol. 293(1), pages 312-335.
    17. Pouraliakbari-Mamaghani, Mahsa & Saif, Ahmed & Kamal, Noreen, 2023. "Reliable design of a congested disaster relief network: A two-stage stochastic-robust optimization approach," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    18. Xuehong Gao, 2022. "A bi-level stochastic optimization model for multi-commodity rebalancing under uncertainty in disaster response," Annals of Operations Research, Springer, vol. 319(1), pages 115-148, December.
    19. Mohsen Yahyaei & Ali Bozorgi-Amiri, 2019. "Robust reliable humanitarian relief network design: an integration of shelter and supply facility location," Annals of Operations Research, Springer, vol. 283(1), pages 897-916, December.
    20. TURKEŠ, Renata & SÖRENSEN, Kenneth, 2018. "Case studies and random instances for the problem of pre-positioning emergency supplies," Working Papers 2018004, University of Antwerp, Faculty of Business and Economics.
    21. Seyed Reza Abazari & Fariborz Jolai & Amir Aghsami, 2022. "Designing a humanitarian relief network considering governmental and non-governmental operations under uncertainty," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1430-1452, June.
    22. Yusen Ye & Wen Jiao & Hong Yan, 2020. "Managing Relief Inventories Responding to Natural Disasters: Gaps Between Practice and Literature," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 807-832, April.
    23. Miguel A. Lejeune & François Margot, 2016. "Solving Chance-Constrained Optimization Problems with Stochastic Quadratic Inequalities," Operations Research, INFORMS, vol. 64(4), pages 939-957, August.
    24. Kınay, Ömer Burak & Yetis Kara, Bahar & Saldanha-da-Gama, Francisco & Correia, Isabel, 2018. "Modeling the shelter site location problem using chance constraints: A case study for Istanbul," European Journal of Operational Research, Elsevier, vol. 270(1), pages 132-145.
    25. Kathryn M. Schumacher & Richard Li‐Yang Chen & Amy E.M. Cohn & Jeremy Castaing, 2016. "Algorithm to solve a chance‐constrained network capacity design problem with stochastic demands and finite support," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(3), pages 236-246, April.
    26. Elçi, Özgün & Noyan, Nilay, 2018. "A chance-constrained two-stage stochastic programming model for humanitarian relief network design," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 55-83.
    27. Liu, Kanglin & Zhang, Hengliang & Zhang, Zhi-Hai, 2021. "The efficiency, equity and effectiveness of location strategies in humanitarian logistics: A robust chance-constrained approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    28. Renata Turkeš & Daniel Palhazi Cuervo & Kenneth Sörensen, 2019. "Pre-positioning of emergency supplies: does putting a price on human life help to save lives?," Annals of Operations Research, Springer, vol. 283(1), pages 865-895, December.
    29. Esteban Ogazón & Neale R. Smith & Angel Ruiz, 2022. "Reconfiguration of Foodbank Network Logistics to Cope with a Sudden Disaster," Mathematics, MDPI, vol. 10(9), pages 1-20, April.
    30. TURKEŠ, Renata & SÖRENSEN, Kenneth & PALHAZI CUERVO, Daniel, 2018. "A matheuristic for the pre-positioning of emergency supplies," Working Papers 2018009, University of Antwerp, Faculty of Business and Economics.
    31. Liu, Kanglin & Liu, Changchun & Xiang, Xi & Tian, Zhili, 2023. "Testing facility location and dynamic capacity planning for pandemics with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 304(1), pages 150-168.
    32. Sengul Orgut, Irem & Freeman, Nickolas & Lewis, Dwight & Parton, Jason, 2023. "Equitable and effective vaccine access considering vaccine hesitancy and capacity constraints," Omega, Elsevier, vol. 120(C).
    33. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.

  16. Bagchi, Prabir & Lejeune, Miguel A. & Alam, A., 2014. "How supply competency affects FDI decisions: Some insights," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 239-251.

    Cited by:

    1. D׳Souza, Derrick E. & Kulkarni, Shailesh S., 2015. "A framework and model for absorptive capacity in a dynamic multi-firm environment," International Journal of Production Economics, Elsevier, vol. 167(C), pages 50-62.
    2. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    3. Kinra, Aseem, 2015. "Environmental complexity related information for the assessment of country logistics environments: Implications for spatial transaction costs and foreign location attractiveness," Journal of Transport Geography, Elsevier, vol. 43(C), pages 36-47.
    4. Balram Avittathur & Jayanth Jayaram, 2016. "Supply chain management in emerging economies," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(2), pages 117-124, June.
    5. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    6. Han, Sang Yun & Bae, Sung Joo, 2014. "Internalization of R&D outsourcing: An empirical study," International Journal of Production Economics, Elsevier, vol. 150(C), pages 58-73.
    7. Halaszovich, Tilo F. & Kinra, Aseem, 2020. "The impact of distance, national transportation systems and logistics performance on FDI and international trade patterns: Results from Asian global value chains," Transport Policy, Elsevier, vol. 98(C), pages 35-47.

  17. Tiago P. Filomena & Miguel A. Lejeune, 2014. "Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 308-329, April.

    Cited by:

    1. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.
    2. Moarefdoost, M. Mohsen & Lamadrid, Alberto J. & Zuluaga, Luis F., 2016. "A robust model for the ramp-constrained economic dispatch problem with uncertain renewable energy," Energy Economics, Elsevier, vol. 56(C), pages 310-325.
    3. Ran Ji & Miguel A. Lejeune & Srinivas Y. Prasad, 2017. "Properties, formulations, and algorithms for portfolio optimization using Mean-Gini criteria," Annals of Operations Research, Springer, vol. 248(1), pages 305-343, January.
    4. Panos Xidonas & Christis Hassapis & George Mavrotas & Christos Staikouras & Constantin Zopounidis, 2018. "Multiobjective portfolio optimization: bridging mathematical theory with asset management practice," Annals of Operations Research, Springer, vol. 267(1), pages 585-606, August.
    5. Sant’Anna, Leonardo R. & Filomena, Tiago P. & Caldeira, João F., 2017. "Index tracking and enhanced indexing using cointegration and correlation with endogenous portfolio selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 146-157.
    6. Leonardo Riegel Sant’Anna & Tiago Pascoal Filomena & Pablo Cristini Guedes & Denis Borenstein, 2017. "Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming," Annals of Operations Research, Springer, vol. 258(2), pages 849-867, November.

  18. Batta, Rajan & Lejeune, Miguel & Prasad, Srinivas, 2014. "Public facility location using dispersion, population, and equity criteria," European Journal of Operational Research, Elsevier, vol. 234(3), pages 819-829.

    Cited by:

    1. Wu, Shanhua & Yang, Zhongzhen, 2018. "Locating manufacturing industries by flow-capturing location model – Case of Chinese steel industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 1-11.
    2. Mingyu Kim & Rajan Batta & Qing He, 2016. "Optimal routing of infiltration operations," Journal of Transportation Security, Springer, vol. 9(1), pages 87-104, June.
    3. Hammad, Ahmed W A & Akbarnezhad, Ali & Rey, David, 2017. "Sustainable urban facility location: Minimising noise pollution and network congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 38-59.
    4. Niblett, Matthew R. & Church, Richard L., 2015. "The disruptive anti-covering location problem," European Journal of Operational Research, Elsevier, vol. 247(3), pages 764-773.
    5. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    6. Liying Yan & Manel Grifoll & Hongxiang Feng & Pengjun Zheng & Chunliang Zhou, 2022. "Optimization of Urban Distribution Centres: A Multi-Stage Dynamic Location Approach," Sustainability, MDPI, vol. 14(7), pages 1-16, March.
    7. Yoon Ha Lee & Ji Soo Lee & Seung Chan Baek & Won Hwa Hong, 2020. "Spatial Equity with Census Population Data vs. Floating Population Data: The Distribution of Earthquake Evacuation Shelters in Daegu, South Korea," Sustainability, MDPI, vol. 12(19), pages 1-17, September.
    8. Maria Barbati & Giuseppe Bruno & Alfredo Marín, 2016. "Balancing the arrival times of users in a two-stage location problem," Annals of Operations Research, Springer, vol. 246(1), pages 273-288, November.
    9. Meltem Peker & Bahar Y. Kara & James F. Campbell & Sibel A. Alumur, 2016. "Spatial Analysis of Single Allocation Hub Location Problems," Networks and Spatial Economics, Springer, vol. 16(4), pages 1075-1101, December.
    10. Soheil Davari & Kemal Kilic & Gurdal Ertek, 2015. "Fuzzy bi-objective preventive health care network design," Health Care Management Science, Springer, vol. 18(3), pages 303-317, September.
    11. Chung, Byung Do & Park, Sungjae & Kwon, Changhyun, 2018. "Equitable distribution of recharging stations for electric vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 1-11.
    12. Colmenar, J. Manuel & Greistorfer, Peter & Martí, Rafael & Duarte, Abraham, 2016. "Advanced Greedy Randomized Adaptive Search Procedure for the Obnoxious p-Median problem," European Journal of Operational Research, Elsevier, vol. 252(2), pages 432-442.
    13. Argyris, Nikolaos & Karsu, Özlem & Yavuz, Mirel, 2022. "Fair resource allocation: Using welfare-based dominance constraints," European Journal of Operational Research, Elsevier, vol. 297(2), pages 560-578.

  19. Lejeune, Miguel A., 2013. "Probabilistic modeling of multiperiod service levels," European Journal of Operational Research, Elsevier, vol. 230(2), pages 299-312.

    Cited by:

    1. Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.
    2. Preece, Gary & Shaw, Duncan & Hayashi, Haruo, 2015. "Application of the Viable System Model to analyse communications structures: A case study of disaster response in Japan," European Journal of Operational Research, Elsevier, vol. 243(1), pages 312-322.
    3. Yin, Zhe & Ma, Shihua, 2015. "Incentives to improve the service level in a random yield supply chain: The role of bonus contracts," European Journal of Operational Research, Elsevier, vol. 244(3), pages 778-791.

  20. Miguel Lejeune, 2012. "Pattern definition of the p-efficiency concept," Annals of Operations Research, Springer, vol. 200(1), pages 23-36, November.

    Cited by:

    1. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    2. Miguel A. Lejeune, 2012. "Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems," Operations Research, INFORMS, vol. 60(6), pages 1356-1372, December.
    3. Lejeune, Miguel A. & Shen, Siqian, 2016. "Multi-objective probabilistically constrained programs with variable risk: Models for multi-portfolio financial optimization," European Journal of Operational Research, Elsevier, vol. 252(2), pages 522-539.
    4. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.
    5. Lejeune, Miguel A., 2013. "Probabilistic modeling of multiperiod service levels," European Journal of Operational Research, Elsevier, vol. 230(2), pages 299-312.
    6. Lukáš Adam & Martin Branda & Holger Heitsch & René Henrion, 2020. "Solving joint chance constrained problems using regularization and Benders’ decomposition," Annals of Operations Research, Springer, vol. 292(2), pages 683-709, September.

  21. Miguel A. Lejeune, 2012. "Game Theoretical Approach for Reliable Enhanced Indexation," Decision Analysis, INFORMS, vol. 9(2), pages 146-155, June.

    Cited by:

    1. Spiridon Penev & Pavel Shevchenko & Wei Wu, 2019. "Myopic robust index tracking with Bregman divergence," Papers 1908.07659, arXiv.org, revised Jul 2021.
    2. Jason R. W. Merrick & Fabrizio Ruggeri & Refik Soyer & L. Robin Keller, 2012. "From the Editors---Games and Decisions in Reliability and Risk," Decision Analysis, INFORMS, vol. 9(2), pages 81-85, June.
    3. Andrea C. Hupman & Jay Simon, 2023. "The Legacy of Peter Fishburn: Foundational Work and Lasting Impact," Decision Analysis, INFORMS, vol. 20(1), pages 1-15, March.
    4. Patrizia Beraldi & Maria Elena Bruni, 2022. "Enhanced indexation via chance constraints," Operational Research, Springer, vol. 22(2), pages 1553-1573, April.
    5. Fengmin Xu & Meihua Wang & Yu-Hong Dai & Dachuan Xu, 2018. "A sparse enhanced indexation model with chance and cardinality constraints," Journal of Global Optimization, Springer, vol. 70(1), pages 5-25, January.
    6. Zhiping Chen & Shen Peng & Abdel Lisser, 2020. "A sparse chance constrained portfolio selection model with multiple constraints," Journal of Global Optimization, Springer, vol. 77(4), pages 825-852, August.
    7. Li, Xuepeng & Xu, Fengmin & Jing, Kui, 2022. "Robust enhanced indexation with ESG: An empirical study in the Chinese Stock Market," Economic Modelling, Elsevier, vol. 107(C).
    8. Ali Yekkehkhany & Timothy Murray & Rakesh Nagi, 2021. "Stochastic Superiority Equilibrium in Game Theory," Decision Analysis, INFORMS, vol. 18(2), pages 153-168, June.
    9. H Mezali & J E Beasley, 2013. "Quantile regression for index tracking and enhanced indexation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(11), pages 1676-1692, November.
    10. Zhiping Chen & Xinkai Zhuang & Jia Liu, 2019. "A Sustainability-Oriented Enhanced Indexation Model with Regime Switching and Cardinality Constraint," Sustainability, MDPI, vol. 11(15), pages 1-14, July.
    11. Tingting Yang & Xiaoxia Huang, 2022. "A New Portfolio Optimization Model Under Tracking-Error Constraint with Linear Uncertainty Distributions," Journal of Optimization Theory and Applications, Springer, vol. 195(2), pages 723-747, November.
    12. Gaustaroba, Gianfranco & Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Linear Programming Models based on Omega Ratio for the Enhanced Index Tracking Problem," MPRA Paper 67097, University Library of Munich, Germany.
    13. Filippi, C. & Guastaroba, G. & Speranza, M.G., 2016. "A heuristic framework for the bi-objective enhanced index tracking problem," Omega, Elsevier, vol. 65(C), pages 122-137.

  22. Miguel A. Lejeune, 2012. "Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems," Operations Research, INFORMS, vol. 60(6), pages 1356-1372, December.

    Cited by:

    1. Wim Ackooij, 2017. "A comparison of four approaches from stochastic programming for large-scale unit-commitment," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 119-147, March.
    2. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    3. Xiaodi Bai & Jie Sun & Xiaojin Zheng, 2021. "An Augmented Lagrangian Decomposition Method for Chance-Constrained Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1056-1069, July.
    4. Xiao Liu & Simge Küçükyavuz, 2018. "A polyhedral study of the static probabilistic lot-sizing problem," Annals of Operations Research, Springer, vol. 261(1), pages 233-254, February.
    5. Hsia, Yong & Wu, Baiyi & Li, Duan, 2014. "New reformulations for probabilistically constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 233(3), pages 550-556.
    6. Lejeune, Miguel A. & Shen, Siqian, 2016. "Multi-objective probabilistically constrained programs with variable risk: Models for multi-portfolio financial optimization," European Journal of Operational Research, Elsevier, vol. 252(2), pages 522-539.
    7. B. K. Pagnoncelli & D. Reich & M. C. Campi, 2012. "Risk-Return Trade-off with the Scenario Approach in Practice: A Case Study in Portfolio Selection," Journal of Optimization Theory and Applications, Springer, vol. 155(2), pages 707-722, November.
    8. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.
    9. Lejeune, Miguel A., 2013. "Probabilistic modeling of multiperiod service levels," European Journal of Operational Research, Elsevier, vol. 230(2), pages 299-312.
    10. Miguel Lejeune, 2012. "Pattern definition of the p-efficiency concept," Annals of Operations Research, Springer, vol. 200(1), pages 23-36, November.
    11. Balbás, Alejandro & Balbás, Beatriz & Balbás, Raquel, 2017. "Differential equations connecting VaR and CVaR," INDEM - Working Paper Business Economic Series 24017, Instituto para el Desarrollo Empresarial (INDEM).
    12. Zheng, Xiaojin & Wu, Baiyi & Cui, Xueting, 2017. "Cell-and-bound algorithm for chance constrained programs with discrete distributions," European Journal of Operational Research, Elsevier, vol. 260(2), pages 421-431.
    13. Gianpiero Canessa & Julian A. Gallego & Lewis Ntaimo & Bernardo K. Pagnoncelli, 2019. "An algorithm for binary linear chance-constrained problems using IIS," Computational Optimization and Applications, Springer, vol. 72(3), pages 589-608, April.
    14. Lukáš Adam & Martin Branda, 2016. "Nonlinear Chance Constrained Problems: Optimality Conditions, Regularization and Solvers," Journal of Optimization Theory and Applications, Springer, vol. 170(2), pages 419-436, August.

  23. Miguel Lejeune, 2011. "A VaR Black–Litterman model for the construction of absolute return fund-of-funds," Quantitative Finance, Taylor & Francis Journals, vol. 11(10), pages 1489-1501.

    Cited by:

    1. B. K. Pagnoncelli & D. Reich & M. C. Campi, 2012. "Risk-Return Trade-off with the Scenario Approach in Practice: A Case Study in Portfolio Selection," Journal of Optimization Theory and Applications, Springer, vol. 155(2), pages 707-722, November.
    2. Zagaglia, Paolo, 2014. "International portfolio allocation with European fixed-income funds: What scope for Italian funds?," MPRA Paper 57878, University Library of Munich, Germany.
    3. Tiago P. Filomena & Miguel A. Lejeune, 2014. "Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 308-329, April.
    4. Valle, C.A. & Meade, N. & Beasley, J.E., 2014. "Absolute return portfolios," Omega, Elsevier, vol. 45(C), pages 20-41.
    5. Miguel A. Lejeune, 2012. "Game Theoretical Approach for Reliable Enhanced Indexation," Decision Analysis, INFORMS, vol. 9(2), pages 146-155, June.

  24. Miguel Lejeune & François Margot, 2011. "Optimization for simulation: LAD accelerator," Annals of Operations Research, Springer, vol. 188(1), pages 285-305, August.

    Cited by:

    1. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    2. Bagchi, Prabir & Lejeune, Miguel A. & Alam, A., 2014. "How supply competency affects FDI decisions: Some insights," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 239-251.
    3. Travaughn C. Bain & Juan F. Avila-Herrera & Ersoy Subasi & Munevver Mine Subasi, 2020. "Logical analysis of multiclass data with relaxed patterns," Annals of Operations Research, Springer, vol. 287(1), pages 11-35, April.

  25. P. Hammer & A. Kogan & M. Lejeune, 2011. "Reverse-engineering country risk ratings: a combinatorial non-recursive model," Annals of Operations Research, Springer, vol. 188(1), pages 185-213, August.

    Cited by:

    1. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    2. Sergey SVESHNIKOV & Victor BOCHARNIKOV, 2009. "Modeling Risk Of International Country Relations," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 4(4(10)_Win), pages 558-569.
    3. Janostik, Radek & Konecny, Jan & Krajča, Petr, 2020. "Interface between Logical Analysis of Data and Formal Concept Analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 792-800.
    4. Bagchi, Prabir & Lejeune, Miguel A. & Alam, A., 2014. "How supply competency affects FDI decisions: Some insights," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 239-251.
    5. Chun-An Chou & Tibérius O. Bonates & Chungmok Lee & Wanpracha Art Chaovalitwongse, 2017. "Multi-pattern generation framework for logical analysis of data," Annals of Operations Research, Springer, vol. 249(1), pages 329-349, February.
    6. Nikola Gradojevic, 2021. "Brexit and foreign exchange market expectations: Could it have been predicted?," Annals of Operations Research, Springer, vol. 297(1), pages 167-189, February.
    7. Travaughn C. Bain & Juan F. Avila-Herrera & Ersoy Subasi & Munevver Mine Subasi, 2020. "Logical analysis of multiclass data with relaxed patterns," Annals of Operations Research, Springer, vol. 287(1), pages 11-35, April.
    8. Cavusgil, S. Tamer & Deligonul, Seyda & Ghauri, Pervez N. & Bamiatzi, Vassiliki & Park, Byung Il & Mellahi, Kamel, 2020. "Risk in international business and its mitigation," Journal of World Business, Elsevier, vol. 55(2).
    9. Miguel Lejeune & François Margot, 2011. "Optimization for simulation: LAD accelerator," Annals of Operations Research, Springer, vol. 188(1), pages 285-305, August.

  26. Lejeune, Miguel & Noyan, Nilay, 2010. "Mathematical programming approaches for generating p-efficient points," European Journal of Operational Research, Elsevier, vol. 207(2), pages 590-600, December.

    Cited by:

    1. Darinka Dentcheva & Gabriela Martinez, 2012. "Augmented Lagrangian method for probabilistic optimization," Annals of Operations Research, Springer, vol. 200(1), pages 109-130, November.
    2. Miguel A. Lejeune, 2012. "Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems," Operations Research, INFORMS, vol. 60(6), pages 1356-1372, December.
    3. Xiaodi Bai & Jie Sun & Xiaojin Zheng, 2021. "An Augmented Lagrangian Decomposition Method for Chance-Constrained Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1056-1069, July.
    4. Zheng, Xiaojin & Sun, Xiaoling & Li, Duan & Cui, Xueting, 2012. "Lagrangian decomposition and mixed-integer quadratic programming reformulations for probabilistically constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 221(1), pages 38-48.
    5. Lejeune, Miguel A., 2013. "Probabilistic modeling of multiperiod service levels," European Journal of Operational Research, Elsevier, vol. 230(2), pages 299-312.
    6. András Prékopa & Merve Unuvar, 2015. "Single Commodity Stochastic Network Design Under Probabilistic Constraint with Discrete Random Variables," Operations Research, INFORMS, vol. 63(6), pages 1512-1527, December.
    7. Miguel Lejeune, 2012. "Pattern definition of the p-efficiency concept," Annals of Operations Research, Springer, vol. 200(1), pages 23-36, November.
    8. Gianpiero Canessa & Julian A. Gallego & Lewis Ntaimo & Bernardo K. Pagnoncelli, 2019. "An algorithm for binary linear chance-constrained problems using IIS," Computational Optimization and Applications, Springer, vol. 72(3), pages 589-608, April.
    9. Edmonds, Lawryn & Derby, Melanie & Hill, Mary & Wu, Hongyu, 2021. "Coordinated operation of water and electricity distribution networks with variable renewable energy and distribution locational marginal pricing," Renewable Energy, Elsevier, vol. 177(C), pages 1438-1450.
    10. Faqiry, M. Nazif & Edmonds, Lawryn & Wu, Hongyu & Pahwa, Anil, 2020. "Distribution locational marginal price-based transactive day-ahead market with variable renewable generation," Applied Energy, Elsevier, vol. 259(C).
    11. Lukáš Adam & Martin Branda & Holger Heitsch & René Henrion, 2020. "Solving joint chance constrained problems using regularization and Benders’ decomposition," Annals of Operations Research, Springer, vol. 292(2), pages 683-709, September.

  27. P. Bonami & M. A. Lejeune, 2009. "An Exact Solution Approach for Portfolio Optimization Problems Under Stochastic and Integer Constraints," Operations Research, INFORMS, vol. 57(3), pages 650-670, June.

    Cited by:

    1. Eduardo Bered Fernandes Vieira & Tiago Pascoal Filomena, 2020. "Liquidity Constraints for Portfolio Selection Based on Financial Volume," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 1055-1077, December.
    2. Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.
    3. Stefan Gerhold & Paul Kruhner, 2017. "Dynamic trading under integer constraints," Papers 1708.07661, arXiv.org.
    4. Vanita Garg & Kusum Deep, 2019. "Portfolio optimization using Laplacian biogeography based optimization," OPSEARCH, Springer;Operational Research Society of India, vol. 56(4), pages 1117-1141, December.
    5. Alexander Vinel & Pavlo Krokhmal, 2014. "On Valid Inequalities for Mixed Integer p-Order Cone Programming," Journal of Optimization Theory and Applications, Springer, vol. 160(2), pages 439-456, February.
    6. Martin Branda & Max Bucher & Michal Červinka & Alexandra Schwartz, 2018. "Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization," Computational Optimization and Applications, Springer, vol. 70(2), pages 503-530, June.
    7. Zhou, Zhongbao & Jin, Qianying & Xiao, Helu & Wu, Qian & Liu, Wenbin, 2018. "Estimation of cardinality constrained portfolio efficiency via segmented DEA," Omega, Elsevier, vol. 76(C), pages 28-37.
    8. Massol, Olivier & Banal-Estañol, Albert, 2014. "Export diversification through resource-based industrialization: The case of natural gas," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1067-1082.
    9. Alper Atamtürk & Hyemin Jeon, 2019. "Lifted polymatroid inequalities for mean-risk optimization with indicator variables," Journal of Global Optimization, Springer, vol. 73(4), pages 677-699, April.
    10. Ran Ji & Miguel A. Lejeune, 2021. "Data-Driven Optimization of Reward-Risk Ratio Measures," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1120-1137, July.
    11. Shijie Liu & Andrew Adams & Boulis M. Ibrahim, 2013. "Effects of Tax on Investment Portfolios and Financial Markets Under Mixed Integer Stochastic Programming," CFI Discussion Papers 1304, Centre for Finance and Investment, Heriot Watt University.
    12. Hsia, Yong & Wu, Baiyi & Li, Duan, 2014. "New reformulations for probabilistically constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 233(3), pages 550-556.
    13. Kay Giesecke & Baeho Kim & Jack Kim & Gerry Tsoukalas, 2014. "Optimal Credit Swap Portfolios," Management Science, INFORMS, vol. 60(9), pages 2291-2307, September.
    14. Murray, Chase C. & Talukdar, Debabrata & Gosavi, Abhijit, 2010. "Joint Optimization of Product Price, Display Orientation and Shelf-Space Allocation in Retail Category Management," Journal of Retailing, Elsevier, vol. 86(2), pages 125-136.
    15. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    16. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.
    17. Ralph Steuer & Markus Hirschberger & Kalyanmoy Deb, 2016. "Extracting from the relaxed for large-scale semi-continuous variable nondominated frontiers," Journal of Global Optimization, Springer, vol. 64(1), pages 33-48, January.
    18. X. Cui & X. Zheng & S. Zhu & X. Sun, 2013. "Convex relaxations and MIQCQP reformulations for a class of cardinality-constrained portfolio selection problems," Journal of Global Optimization, Springer, vol. 56(4), pages 1409-1423, August.
    19. Tiago P. Filomena & Miguel A. Lejeune, 2014. "Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 308-329, April.
    20. Zheng, Xiaojin & Sun, Xiaoling & Li, Duan & Cui, Xueting, 2012. "Lagrangian decomposition and mixed-integer quadratic programming reformulations for probabilistically constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 221(1), pages 38-48.
    21. Xiaojin Zheng & Xiaoling Sun & Duan Li & Jie Sun, 2014. "Successive convex approximations to cardinality-constrained convex programs: a piecewise-linear DC approach," Computational Optimization and Applications, Springer, vol. 59(1), pages 379-397, October.
    22. Moarefdoost, M. Mohsen & Lamadrid, Alberto J. & Zuluaga, Luis F., 2016. "A robust model for the ramp-constrained economic dispatch problem with uncertain renewable energy," Energy Economics, Elsevier, vol. 56(C), pages 310-325.
    23. Ran Ji & Miguel A. Lejeune & Srinivas Y. Prasad, 2017. "Properties, formulations, and algorithms for portfolio optimization using Mean-Gini criteria," Annals of Operations Research, Springer, vol. 248(1), pages 305-343, January.
    24. Miguel A. Lejeune, 2012. "Game Theoretical Approach for Reliable Enhanced Indexation," Decision Analysis, INFORMS, vol. 9(2), pages 146-155, June.
    25. Kyle Steinhauer & Takahisa Fukadai & Sho Yoshida, 2020. "Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation," Papers 2009.08412, arXiv.org.
    26. Liu, Kanglin & Li, Qiaofeng & Zhang, Zhi-Hai, 2019. "Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 79-101.
    27. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2011. "Heuristic algorithms for the cardinality constrained efficient frontier," European Journal of Operational Research, Elsevier, vol. 213(3), pages 538-550, September.
    28. Stefan Gerhold & Paul Krühner, 2018. "Dynamic trading under integer constraints," Finance and Stochastics, Springer, vol. 22(4), pages 919-957, October.
    29. Zhe Liu & Shurong Li, 2022. "A numerical method for interval multi-objective mixed-integer optimal control problems based on quantum heuristic algorithm," Annals of Operations Research, Springer, vol. 311(2), pages 853-898, April.
    30. Jongbin Jung & Seongmoon Kim, 2017. "Developing a dynamic portfolio selection model with a self-adjusted rebalancing method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 766-779, July.
    31. Miten Mistry & Dimitrios Letsios & Gerhard Krennrich & Robert M. Lee & Ruth Misener, 2021. "Mixed-Integer Convex Nonlinear Optimization with Gradient-Boosted Trees Embedded," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1103-1119, July.
    32. Liu, Kanglin & Zhang, Zhi-Hai, 2018. "Capacitated disassembly scheduling under stochastic yield and demand," European Journal of Operational Research, Elsevier, vol. 269(1), pages 244-257.
    33. Gili Rosenberg & Poya Haghnegahdar & Phil Goddard & Peter Carr & Kesheng Wu & Marcos L'opez de Prado, 2015. "Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer," Papers 1508.06182, arXiv.org, revised Aug 2016.
    34. Panos Xidonas & Christis Hassapis & George Mavrotas & Christos Staikouras & Constantin Zopounidis, 2018. "Multiobjective portfolio optimization: bridging mathematical theory with asset management practice," Annals of Operations Research, Springer, vol. 267(1), pages 585-606, August.
    35. Vedat Bayram & Hande Yaman, 2018. "Shelter Location and Evacuation Route Assignment Under Uncertainty: A Benders Decomposition Approach," Transportation Science, INFORMS, vol. 52(2), pages 416-436, March.
    36. Dorsaf Cherif & Meriam El Mansour & Emmanuel Lepinette, 2023. "A short note on super-hedging an arbitrary number of European options with integer-valued strategies," Papers 2311.08871, arXiv.org.
    37. Carina Moreira Costa & Dennis Kreber & Martin Schmidt, 2022. "An Alternating Method for Cardinality-Constrained Optimization: A Computational Study for the Best Subset Selection and Sparse Portfolio Problems," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 2968-2988, November.
    38. Miguel A. Lejeune & François Margot, 2016. "Solving Chance-Constrained Optimization Problems with Stochastic Quadratic Inequalities," Operations Research, INFORMS, vol. 64(4), pages 939-957, August.
    39. Patrizia Beraldi & Maria Bruni & Antonio Violi, 2012. "Capital rationing problems under uncertainty and risk," Computational Optimization and Applications, Springer, vol. 51(3), pages 1375-1396, April.
    40. Zhang, Zhi-Hai & Unnikrishnan, Avinash, 2016. "A coordinated location-inventory problem in closed-loop supply chain," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 127-148.
    41. Fereshteh Vaezi & Seyed Jafar Sadjadi & Ahmad Makui, 2019. "A portfolio selection model based on the knapsack problem under uncertainty," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-19, May.
    42. Philipp Baumann & Norbert Trautmann, 2013. "Portfolio-optimization models for small investors," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 345-356, June.
    43. Xueting Cui & Xiaoling Sun & Shushang Zhu & Rujun Jiang & Duan Li, 2018. "Portfolio Optimization with Nonparametric Value at Risk: A Block Coordinate Descent Method," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 454-471, August.
    44. Chien-Ming Chen & Joe Zhu, 2011. "Efficient Resource Allocation via Efficiency Bootstraps: An Application to R&D Project Budgeting," Operations Research, INFORMS, vol. 59(3), pages 729-741, June.
    45. Todor Stoilov & Krasimira Stoilova & Miroslav Vladimirov, 2021. "Explicit Value at Risk Goal Function in Bi-Level Portfolio Problem for Financial Sustainability," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    46. Dimitris Bertsimas & Ryan Cory-Wright, 2022. "A Scalable Algorithm for Sparse Portfolio Selection," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1489-1511, May.
    47. Mike G. Tsionas & Dionisis Philippas & Constantin Zopounidis, 2023. "Exploring Uncertainty, Sensitivity and Robust Solutions in Mathematical Programming Through Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 205-227, June.
    48. Jianjun Gao & Duan Li, 2013. "Optimal Cardinality Constrained Portfolio Selection," Operations Research, INFORMS, vol. 61(3), pages 745-761, June.
    49. Amir Ahmadi-Javid & Pooya Hoseinpour, 2022. "Convexification of Queueing Formulas by Mixed-Integer Second-Order Cone Programming: An Application to a Discrete Location Problem with Congestion," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2621-2633, September.

  28. Miguel A. Lejeune & Nevena Yakova, 2008. "Showcase Scheduling at Fred Astaire East Side Dance Studio," Interfaces, INFORMS, vol. 38(3), pages 176-186, June.

    Cited by:

    1. J. Paul Brooks, 2012. "The Court of Appeals of Virginia Uses Integer Programming and Cloud Computing to Schedule Sessions," Interfaces, INFORMS, vol. 42(6), pages 544-553, December.

  29. M A Lejeune, 2008. "Preprocessing techniques and column generation algorithms for stochastically efficient demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1239-1252, September.

    Cited by:

    1. Miguel A. Lejeune, 2012. "Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems," Operations Research, INFORMS, vol. 60(6), pages 1356-1372, December.
    2. Miguel Lejeune, 2012. "Pattern definition of the p-efficiency concept," Annals of Operations Research, Springer, vol. 200(1), pages 23-36, November.

  30. Miguel A. Lejeune & Andrzej Ruszczyński, 2007. "An Efficient Trajectory Method for Probabilistic Production-Inventory-Distribution Problems," Operations Research, INFORMS, vol. 55(2), pages 378-394, April.

    Cited by:

    1. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.
    2. Miguel A. Lejeune, 2012. "Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems," Operations Research, INFORMS, vol. 60(6), pages 1356-1372, December.
    3. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "A tactical supply chain planning model with multiple flexibility options: an empirical evaluation," Annals of Operations Research, Springer, vol. 244(2), pages 429-454, September.
    4. Xiao Liu & Simge Küçükyavuz, 2018. "A polyhedral study of the static probabilistic lot-sizing problem," Annals of Operations Research, Springer, vol. 261(1), pages 233-254, February.
    5. Lejeune, Miguel A. & Shen, Siqian, 2016. "Multi-objective probabilistically constrained programs with variable risk: Models for multi-portfolio financial optimization," European Journal of Operational Research, Elsevier, vol. 252(2), pages 522-539.
    6. L. Jeff Hong & Zhiyuan Huang & Henry Lam, 2021. "Learning-Based Robust Optimization: Procedures and Statistical Guarantees," Management Science, INFORMS, vol. 67(6), pages 3447-3467, June.
    7. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "Tactical supply chain planning models with inherent flexibility: definition and review," Annals of Operations Research, Springer, vol. 244(2), pages 407-427, September.
    8. Miguel Lejeune, 2012. "Pattern definition of the p-efficiency concept," Annals of Operations Research, Springer, vol. 200(1), pages 23-36, November.
    9. Yugang Yu & Chengbin Chu & Haoxun Chen & Feng Chu, 2012. "Large scale stochastic inventory routing problems with split delivery and service level constraints," Annals of Operations Research, Springer, vol. 197(1), pages 135-158, August.
    10. Zhang, Dali & Xu, Huifu & Wu, Yue, 2009. "Single and multi-period optimal inventory control models with risk-averse constraints," European Journal of Operational Research, Elsevier, vol. 199(2), pages 420-434, December.
    11. Zheng, Xiaojin & Wu, Baiyi & Cui, Xueting, 2017. "Cell-and-bound algorithm for chance constrained programs with discrete distributions," European Journal of Operational Research, Elsevier, vol. 260(2), pages 421-431.
    12. Lejeune, Miguel & Noyan, Nilay, 2010. "Mathematical programming approaches for generating p-efficient points," European Journal of Operational Research, Elsevier, vol. 207(2), pages 590-600, December.
    13. Yu, Y. & Chu, C. & Chen, H.X. & Chu, F., 2010. "Linearization and Decomposition Methods for Large Scale Stochastic Inventory Routing Problem with Service Level Constraints," ERIM Report Series Research in Management ERS-2010-008-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  31. Lejeune, M.A., 2006. "A variable neighborhood decomposition search method for supply chain management planning problems," European Journal of Operational Research, Elsevier, vol. 175(2), pages 959-976, December.

    Cited by:

    1. Quanxi Li & Haowei Zhang & Kailing Liu, 2021. "Research on Closed-Loop Supply Chain Decision-Making in Different Cooperation Modes with Government’s Reward-Penalty Mechanism," Sustainability, MDPI, vol. 13(11), pages 1-22, June.
    2. Anghinolfi, D. & Paolucci, M. & Sacone, S. & Siri, S., 2011. "Freight transportation in railway networks with automated terminals: A mathematical model and MIP heuristic approaches," European Journal of Operational Research, Elsevier, vol. 214(3), pages 588-594, November.
    3. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "A tactical supply chain planning model with multiple flexibility options: an empirical evaluation," Annals of Operations Research, Springer, vol. 244(2), pages 429-454, September.
    4. Yin, Jiateng & D’Ariano, Andrea & Wang, Yihui & Yang, Lixing & Tang, Tao, 2021. "Timetable coordination in a rail transit network with time-dependent passenger demand," European Journal of Operational Research, Elsevier, vol. 295(1), pages 183-202.
    5. Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 705-726, December.
    6. Maiyar, Lohithaksha M. & Thakkar, Jitesh J., 2019. "Modelling and analysis of intermodal food grain transportation under hub disruption towards sustainability," International Journal of Production Economics, Elsevier, vol. 217(C), pages 281-297.
    7. Hassini, Elkafi & Surti, Chirag & Searcy, Cory, 2012. "A literature review and a case study of sustainable supply chains with a focus on metrics," International Journal of Production Economics, Elsevier, vol. 140(1), pages 69-82.
    8. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "Tactical supply chain planning models with inherent flexibility: definition and review," Annals of Operations Research, Springer, vol. 244(2), pages 407-427, September.
    9. Sasan Khalifehzadeh & Mehdi Seifbarghy & Bahman Naderi, 2017. "Solving a fuzzy multi objective model of a production–distribution system using meta-heuristic based approaches," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 95-109, January.
    10. Barbosa-Póvoa, Ana Paula & da Silva, Cátia & Carvalho, Ana, 2018. "Opportunities and challenges in sustainable supply chain: An operations research perspective," European Journal of Operational Research, Elsevier, vol. 268(2), pages 399-431.
    11. Devika, K. & Jafarian, A. & Nourbakhsh, V., 2014. "Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques," European Journal of Operational Research, Elsevier, vol. 235(3), pages 594-615.
    12. Fariba Goodarzian & Ali Navaei & Behdad Ehsani & Peiman Ghasemi & Jesús Muñuzuri, 2023. "Designing an integrated responsive-green-cold vaccine supply chain network using Internet-of-Things: artificial intelligence-based solutions," Annals of Operations Research, Springer, vol. 328(1), pages 531-575, September.
    13. Pierre Hansen & Nenad Mladenović & José Moreno Pérez, 2010. "Variable neighbourhood search: methods and applications," Annals of Operations Research, Springer, vol. 175(1), pages 367-407, March.
    14. Srikant Gupta & Irfan Ali & Aquil Ahmed, 2018. "Multi-objective bi-level supply chain network order allocation problem under fuzziness," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 721-748, November.
    15. Xiong, Fuli & Xing, Keyi & Wang, Feng, 2015. "Scheduling a hybrid assembly-differentiation flowshop to minimize total flow time," European Journal of Operational Research, Elsevier, vol. 240(2), pages 338-354.
    16. Yang Lv & Xinhua Bi & Quanxi Li & Haowei Zhang, 2022. "Research on Closed-Loop Supply Chain Decision Making and Recycling Channel Selection under Carbon Allowance and Carbon Trading," Sustainability, MDPI, vol. 14(18), pages 1-17, September.

  32. Hammer, P.L. & Kogan, A. & Lejeune, M.A., 2006. "Modeling country risk ratings using partial orders," European Journal of Operational Research, Elsevier, vol. 175(2), pages 836-859, December.

    Cited by:

    1. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    2. Miguel A. Lejeune, 2012. "Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems," Operations Research, INFORMS, vol. 60(6), pages 1356-1372, December.
    3. Sun, Xiaolei & Li, Jianping & Tang, Ling & Wu, Dengsheng, 2012. "Identifying the risk-return tradeoff and exploring the dynamic risk exposure of country portfolio of the FSU's oil economies," Economic Modelling, Elsevier, vol. 29(6), pages 2494-2503.
    4. Abroon Qazi & Mecit Can Emre Simsekler, 2022. "Prioritizing interdependent drivers of financial, economic, and political risks using a data-driven probabilistic approach," Risk Management, Palgrave Macmillan, vol. 24(2), pages 164-185, June.
    5. Caserta, Marco & Reiners, Torsten, 2016. "A pool-based pattern generation algorithm for logical analysis of data with automatic fine-tuning," European Journal of Operational Research, Elsevier, vol. 248(2), pages 593-606.
    6. P. Hammer & A. Kogan & M. Lejeune, 2011. "Reverse-engineering country risk ratings: a combinatorial non-recursive model," Annals of Operations Research, Springer, vol. 188(1), pages 185-213, August.
    7. Janostik, Radek & Konecny, Jan & Krajča, Petr, 2020. "Interface between Logical Analysis of Data and Formal Concept Analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 792-800.
    8. Bagchi, Prabir & Lejeune, Miguel A. & Alam, A., 2014. "How supply competency affects FDI decisions: Some insights," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 239-251.
    9. Abdulkerim Karaaslan & Kürşat Özgür Özden, 2017. "Forecasting Turkey’s Credit Ratings with Multivariate Grey Model and Grey Relational Analysis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(3), pages 583-610, September.
    10. Markellos, Raphael N. & Psychoyios, Dimitris & Schneider, Friedrich, 2016. "Sovereign debt markets in light of the shadow economy," European Journal of Operational Research, Elsevier, vol. 252(1), pages 220-231.
    11. Jianping Li & Xiaolei Sun & Fei Wang & Dengsheng Wu, 2015. "Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach," Annals of Operations Research, Springer, vol. 234(1), pages 57-76, November.
    12. Guido Bonatti & Andrea Ciacci & Enrico Ivaldi, 2021. "Different Measures of Country Risk: An Application to European Countries," JRFM, MDPI, vol. 14(1), pages 1-16, January.
    13. Liu, Chang & Sun, Xiaolei & Chen, Jianming & Li, Jianping, 2016. "Statistical properties of country risk ratings under oil price volatility: Evidence from selected oil-exporting countries," Energy Policy, Elsevier, vol. 92(C), pages 234-245.
    14. San Martín Albizuri, Nerea & Rodríguez Castellanos, Arturo, 2008. "¿Reflejan los índices de riesgo país las variables relevantes en el desencadenamiento de las crisis externas? Un análisis sobre el periodo 1994-2001," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).
    15. Dilek Teker & Aynur Pala & Oya Kent, 2013. "Determination of Sovereign Rating: Factor Based Ordered Probit Models for Panel Data Analysis Modelling Framework," International Journal of Economics and Financial Issues, Econjournals, vol. 3(1), pages 122-132.
    16. Peter Hammer & Tibérius Bonates, 2006. "Logical analysis of data—An overview: From combinatorial optimization to medical applications," Annals of Operations Research, Springer, vol. 148(1), pages 203-225, November.
    17. Srđan Jelinek & Pavle Milošević & Aleksandar Rakićević & Ana Poledica & Bratislav Petrović, 2022. "A Novel IBA-DE Hybrid Approach for Modeling Sovereign Credit Ratings," Mathematics, MDPI, vol. 10(15), pages 1-21, July.
    18. Miguel Lejeune & François Margot, 2011. "Optimization for simulation: LAD accelerator," Annals of Operations Research, Springer, vol. 188(1), pages 285-305, August.

  33. Lejeune, Miguel A., 2003. "Heuristic optimization of experimental designs," European Journal of Operational Research, Elsevier, vol. 147(3), pages 484-498, June.

    Cited by:

    1. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2013. "An iterated local search algorithm for the construction of large scale D-optimal experimental designs," Working Papers 2013006, University of Antwerp, Faculty of Business and Economics.
    2. Ioannidis Evangelos & Merkouris Takis & Zhang Li-Chun & Karlberg Martin & Petrakos Michalis & Reis Fernando & Stavropoulos Photis, 2016. "On a Modular Approach to the Design of Integrated Social Surveys," Journal of Official Statistics, Sciendo, vol. 32(2), pages 259-286, June.
    3. Vieira Jr., Hélcio & Sanchez, Susan & Kienitz, Karl Heinz & Belderrain, Mischel Carmen Neyra, 2011. "Generating and improving orthogonal designs by using mixed integer programming," European Journal of Operational Research, Elsevier, vol. 215(3), pages 629-638, December.
    4. Karvanen, Juha & Kulathinal, Sangita & Gasbarra, Dario, 2009. "Optimal designs to select individuals for genotyping conditional on observed binary or survival outcomes and non-genetic covariates," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1782-1793, March.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.