IDEAS home Printed from https://ideas.repec.org/r/eee/ejores/v218y2012i2p470-483.html
   My bibliography  Save this item

Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Alexander Shapiro & Wajdi Tekaya & Murilo Pereira Soares & Joari Paulo da Costa, 2013. "Worst-Case-Expectation Approach to Optimization Under Uncertainty," Operations Research, INFORMS, vol. 61(6), pages 1435-1449, December.
  2. de Queiroz, Anderson Rodrigo, 2016. "Stochastic hydro-thermal scheduling optimization: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 382-395.
  3. Powell, Warren B., 2019. "A unified framework for stochastic optimization," European Journal of Operational Research, Elsevier, vol. 275(3), pages 795-821.
  4. Daniel R. Jiang & Warren B. Powell, 2018. "Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures," Mathematics of Operations Research, INFORMS, vol. 43(2), pages 554-579, May.
  5. Zsolt Bihary & Péter Csóka & Dávid Zoltán Szabó, 2020. "Spectral risk measure of holding stocks in the long run," Annals of Operations Research, Springer, vol. 295(1), pages 75-89, December.
  6. Soares, Murilo Pereira & Street, Alexandre & Valladão, Davi Michel, 2017. "On the solution variability reduction of Stochastic Dual Dynamic Programming applied to energy planning," European Journal of Operational Research, Elsevier, vol. 258(2), pages 743-760.
  7. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
  8. Weini Zhang & Hamed Rahimian & Güzin Bayraksan, 2016. "Decomposition Algorithms for Risk-Averse Multistage Stochastic Programs with Application to Water Allocation under Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 385-404, August.
  9. Homem-de-Mello, Tito & Pagnoncelli, Bernardo K., 2016. "Risk aversion in multistage stochastic programming: A modeling and algorithmic perspective," European Journal of Operational Research, Elsevier, vol. 249(1), pages 188-199.
  10. Escudero Bueno, Laureano F. & Garín Martín, María Araceli & Merino Maestre, María & Pérez Sainz de Rozas, Gloria, 2015. "Some experiments on solving multistage stochastic mixed 0-1 programs with time stochastic dominance constraints," BILTOKI BILTOKI;2015-01, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
  11. Shapiro, Alexander & Tekaya, Wajdi & da Costa, Joari Paulo & Soares, Murilo Pereira, 2013. "Risk neutral and risk averse Stochastic Dual Dynamic Programming method," European Journal of Operational Research, Elsevier, vol. 224(2), pages 375-391.
  12. Bülbül, Kerem & Noyan, Nilay & Erol, Hazal, 2021. "Multi-stage stochastic programming models for provisioning cloud computing resources," European Journal of Operational Research, Elsevier, vol. 288(3), pages 886-901.
  13. Vitor Matos & Mauro Sierra & Erlon Finardi & Brigida Decker & André Milanezi, 2015. "Stochastic model for energy commercialisation of small hydro plants in the Brazilian energy market," Computational Management Science, Springer, vol. 12(1), pages 111-127, January.
  14. Pan, Zhenning & Yu, Tao & Li, Jie & Qu, Kaiping & Yang, Bo, 2020. "Risk-averse real-time dispatch of integrated electricity and heat system using a modified approximate dynamic programming approach," Energy, Elsevier, vol. 198(C).
  15. Singh, Bindeshwar & Mukherjee, V. & Tiwari, Prabhakar, 2015. "A survey on impact assessment of DG and FACTS controllers in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 846-882.
  16. Davi Valladão & Thuener Silva & Marcus Poggi, 2019. "Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns," Annals of Operations Research, Springer, vol. 282(1), pages 379-405, November.
  17. Larissa de Oliveira Resende & Davi Valladão & Bernardo Vieira Bezerra & Yasmin Monteiro Cyrillo, 0. "Assessing the value of natural gas underground storage in the Brazilian system via stochastic dual dynamic programming," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 0, pages 1-19.
  18. Schur, Rouven & Gönsch, Jochen & Hassler, Michael, 2019. "Time-consistent, risk-averse dynamic pricing," European Journal of Operational Research, Elsevier, vol. 277(2), pages 587-603.
  19. Zsolt Bihary & Péter Csóka & Dávid Zoltán Szabó, 0. "Spectral risk measure of holding stocks in the long run," Annals of Operations Research, Springer, vol. 0, pages 1-15.
  20. Pengyu Qian & Zizhuo Wang & Zaiwen Wen, 2015. "A Composite Risk Measure Framework for Decision Making under Uncertainty," Papers 1501.01126, arXiv.org.
  21. Nils Löhndorf & David Wozabal & Stefan Minner, 2013. "Optimizing Trading Decisions for Hydro Storage Systems Using Approximate Dual Dynamic Programming," Operations Research, INFORMS, vol. 61(4), pages 810-823, August.
  22. Daniel F. Salas & Warren B. Powell, 2018. "Benchmarking a Scalable Approximate Dynamic Programming Algorithm for Stochastic Control of Grid-Level Energy Storage," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 106-123, February.
  23. Borodin, Valeria & Bourtembourg, Jean & Hnaien, Faicel & Labadie, Nacima, 2015. "A multi-step rolled forward chance-constrained model and a proactive dynamic approach for the wheat crop quality control problem," European Journal of Operational Research, Elsevier, vol. 246(2), pages 631-640.
  24. Fredo, Guilherme Luiz Minetto & Finardi, Erlon Cristian & de Matos, Vitor Luiz, 2019. "Assessing solution quality and computational performance in the long-term generation scheduling problem considering different hydro production function approaches," Renewable Energy, Elsevier, vol. 131(C), pages 45-54.
  25. Rudloff, Birgit & Street, Alexandre & Valladão, Davi M., 2014. "Time consistency and risk averse dynamic decision models: Definition, interpretation and practical consequences," European Journal of Operational Research, Elsevier, vol. 234(3), pages 743-750.
  26. Andy Philpott & Vitor de Matos & Erlon Finardi, 2013. "On Solving Multistage Stochastic Programs with Coherent Risk Measures," Operations Research, INFORMS, vol. 61(4), pages 957-970, August.
  27. Alonso-Ayuso, Antonio & Carvallo, Felipe & Escudero, Laureano F. & Guignard, Monique & Pi, Jiaxing & Puranmalka, Raghav & Weintraub, Andrés, 2014. "Medium range optimization of copper extraction planning under uncertainty in future copper prices," European Journal of Operational Research, Elsevier, vol. 233(3), pages 711-726.
  28. Alois Pichler, 2017. "A quantitative comparison of risk measures," Annals of Operations Research, Springer, vol. 254(1), pages 251-275, July.
  29. Ling, Aifan & Sun, Jie & Xiu, Naihua & Yang, Xiaoguang, 2017. "Robust two-stage stochastic linear optimization with risk aversion," European Journal of Operational Research, Elsevier, vol. 256(1), pages 215-229.
  30. Luckny Zéphyr & C. Lindsay Anderson, 2018. "Stochastic dynamic programming approach to managing power system uncertainty with distributed storage," Computational Management Science, Springer, vol. 15(1), pages 87-110, January.
  31. Pisciella, P. & Vespucci, M.T. & Bertocchi, M. & Zigrino, S., 2016. "A time consistent risk averse three-stage stochastic mixed integer optimization model for power generation capacity expansion," Energy Economics, Elsevier, vol. 53(C), pages 203-211.
  32. Pritchard, Geoffrey, 2015. "Stochastic inflow modeling for hydropower scheduling problems," European Journal of Operational Research, Elsevier, vol. 246(2), pages 496-504.
  33. Duenas, Pablo & Ramos, Andres & Tapia-Ahumada, Karen & Olmos, Luis & Rivier, Michel & Pérez-Arriaga, Jose-Ignacio, 2018. "Security of supply in a carbon-free electric power system: The case of Iceland," Applied Energy, Elsevier, vol. 212(C), pages 443-454.
  34. Zhang, Juheng & Aytug, Haldun, 2016. "Comparison of imputation methods for discriminant analysis with strategically hidden data," European Journal of Operational Research, Elsevier, vol. 255(2), pages 522-530.
  35. Dowson, Oscar & Philpott, Andy & Mason, Andrew & Downward, Anthony, 2019. "A multi-stage stochastic optimization model of a pastoral dairy farm," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1077-1089.
  36. Dominic White & Niven Winchester, 2018. "Energy- and multi-sector modelling of climate change mitigation in New Zealand: current practice and future needs," Working Papers 18_15, Motu Economic and Public Policy Research.
  37. Escudero, Laureano F. & Garín, María Araceli & Merino, María & Pérez, Gloria, 2016. "On time stochastic dominance induced by mixed integer-linear recourse in multistage stochastic programs," European Journal of Operational Research, Elsevier, vol. 249(1), pages 164-176.
  38. Dias, Bruno Henriques & Tomim, Marcelo Aroca & Marcato, André Luís Marques & Ramos, Tales Pulinho & Brandi, Rafael Bruno S. & Junior, Ivo Chaves da Silva & Filho, João Alberto Passos, 2013. "Parallel computing applied to the stochastic dynamic programming for long term operation planning of hydrothermal power systems," European Journal of Operational Research, Elsevier, vol. 229(1), pages 212-222.
  39. Audrius Kabašinskas & Francesca Maggioni & Kristina Šutienė & Eimutis Valakevičius, 2019. "A multistage risk-averse stochastic programming model for personal savings accrual: the evidence from Lithuania," Annals of Operations Research, Springer, vol. 279(1), pages 43-70, August.
  40. W. Ackooij & X. Warin, 2020. "On conditional cuts for stochastic dual dynamic programming," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(2), pages 173-199, June.
  41. Liu, Rui Peng & Shapiro, Alexander, 2020. "Risk neutral reformulation approach to risk averse stochastic programming," European Journal of Operational Research, Elsevier, vol. 286(1), pages 21-31.
  42. Vincent Guigues, 2014. "SDDP for some interstage dependent risk-averse problems and application to hydro-thermal planning," Computational Optimization and Applications, Springer, vol. 57(1), pages 167-203, January.
  43. Zhou, Shaorui & Zhang, Hui & Shi, Ning & Xu, Zhou & Wang, Fan, 2020. "A new convergent hybrid learning algorithm for two-stage stochastic programs," European Journal of Operational Research, Elsevier, vol. 283(1), pages 33-46.
  44. Guigues, Vincent, 2017. "Dual Dynamic Programing with cut selection: Convergence proof and numerical experiments," European Journal of Operational Research, Elsevier, vol. 258(1), pages 47-57.
  45. Vitor L. de Matos & David P. Morton & Erlon C. Finardi, 2017. "Assessing policy quality in a multistage stochastic program for long-term hydrothermal scheduling," Annals of Operations Research, Springer, vol. 253(2), pages 713-731, June.
  46. A. B. Philpott & V. L. Matos & L. Kapelevich, 2018. "Distributionally robust SDDP," Computational Management Science, Springer, vol. 15(3), pages 431-454, October.
  47. 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.
  48. Andre Luiz Diniz & Maria Elvira P. Maceira & Cesar Luis V. Vasconcellos & Debora Dias J. Penna, 2020. "A combined SDDP/Benders decomposition approach with a risk-averse surface concept for reservoir operation in long term power generation planning," Annals of Operations Research, Springer, vol. 292(2), pages 649-681, September.
  49. Jitka Dupačová & Václav Kozmík, 2017. "SDDP for multistage stochastic programs: preprocessing via scenario reduction," Computational Management Science, Springer, vol. 14(1), pages 67-80, January.
  50. Lohmann, Timo & Hering, Amanda S. & Rebennack, Steffen, 2016. "Spatio-temporal hydro forecasting of multireservoir inflows for hydro-thermal scheduling," European Journal of Operational Research, Elsevier, vol. 255(1), pages 243-258.
  51. Löhndorf, Nils & Shapiro, Alexander, 2019. "Modeling time-dependent randomness in stochastic dual dynamic programming," European Journal of Operational Research, Elsevier, vol. 273(2), pages 650-661.
IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.