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Optimization Theory and Methods

Citations

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Cited by:

  1. Li, Jinqing & Ma, Jun, 2019. "Maximum penalized likelihood estimation of additive hazards models with partly interval censoring," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 170-180.
  2. Luis Miguel Pérez Archila & Juan David Bastidas-Rodríguez & Rodrigo Correa & Luz Adriana Trejos Grisales & Daniel Gonzalez-Montoya, 2020. "A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms," Energies, MDPI, vol. 13(4), pages 1-22, February.
  3. Saman Babaie-Kafaki, 2012. "A Quadratic Hybridization of Polak–Ribière–Polyak and Fletcher–Reeves Conjugate Gradient Methods," Journal of Optimization Theory and Applications, Springer, vol. 154(3), pages 916-932, September.
  4. Amin Fahs & Hassane Fahs & R. Dehghani, 2022. "Optimal Scaling Parameters for Spectral Conjugate Gradient Methods," SN Operations Research Forum, Springer, vol. 3(2), pages 1-13, June.
  5. Kin Yau Wong & Qingning Zhou & Tao Hu, 2023. "Semiparametric regression analysis of doubly-censored data with applications to incubation period estimation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 87-114, January.
  6. Ioannis C. Demetriou, 2022. "A binary search algorithm for univariate data approximation and estimation of extrema by piecewise monotonic constraints," Journal of Global Optimization, Springer, vol. 82(4), pages 691-726, April.
  7. Tiantian Zhao & Wei Hong Yang, 2023. "A Nonlinear Conjugate Gradient Method Using Inexact First-Order Information," Journal of Optimization Theory and Applications, Springer, vol. 198(2), pages 502-530, August.
  8. Saha, Tanay & Rakshit, Suman & Khare, Swanand R., 2023. "Linearly structured quadratic model updating using partial incomplete eigendata," Applied Mathematics and Computation, Elsevier, vol. 446(C).
  9. García-Ródenas, Ricardo & García-García, José Carlos & López-Fidalgo, Jesús & Martín-Baos, José Ángel & Wong, Weng Kee, 2020. "A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  10. Vladimir Yu. Protasov & Tatyana I. Zaitseva & Dmitrii O. Logofet, 2022. "Pattern-Multiplicative Average of Nonnegative Matrices: When a Constrained Minimization Problem Requires Versatile Optimization Tools," Mathematics, MDPI, vol. 10(23), pages 1-15, November.
  11. Abolfazl Gharaei & Alireza Amjadian & Ali Shavandi & Amir Amjadian, 2023. "An augmented Lagrangian approach with general constraints to solve nonlinear models of the large-scale reliable inventory systems," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-37, March.
  12. Jörg Fliege & Andrey Tin & Alain Zemkoho, 2021. "Gauss–Newton-type methods for bilevel optimization," Computational Optimization and Applications, Springer, vol. 78(3), pages 793-824, April.
  13. Yan Zhang & Wenyu Sun & Liqun Qi, 2010. "A Nonmonotone Filter Barzilai-Borwein Method For Optimization," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 27(01), pages 55-69.
  14. Wei Bian & Xiaojun Chen, 2017. "Optimality and Complexity for Constrained Optimization Problems with Nonconvex Regularization," Mathematics of Operations Research, INFORMS, vol. 42(4), pages 1063-1084, November.
  15. Trond Steihaug & Sara Suleiman, 2013. "Global convergence and the Powell singular function," Journal of Global Optimization, Springer, vol. 56(3), pages 845-853, July.
  16. Hailin Sun & Huifu Xu & Yong Wang, 2013. "A Smoothing Penalized Sample Average Approximation Method For Stochastic Programs With Second-Order Stochastic Dominance Constraints," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(03), pages 1-25.
  17. Maldonado, Sebastián & López, Julio & Vairetti, Carla, 2020. "Profit-based churn prediction based on Minimax Probability Machines," European Journal of Operational Research, Elsevier, vol. 284(1), pages 273-284.
  18. Petrović, Milena J., 2015. "An Accelerated Double Step Size model in unconstrained optimization," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 309-319.
  19. Vahid Morovati & Hadi Basirzadeh & Latif Pourkarimi, 2018. "Quasi-Newton methods for multiobjective optimization problems," 4OR, Springer, vol. 16(3), pages 261-294, September.
  20. Yong Wang & Guanglu Zhou & Xin Zhang & Wanquan Liu & Louis Caccetta, 2016. "The Non-convex Sparse Problem with Nonnegative Constraint for Signal Reconstruction," Journal of Optimization Theory and Applications, Springer, vol. 170(3), pages 1009-1025, September.
  21. Roozbeh, Mahdi, 2016. "Robust ridge estimator in restricted semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 127-144.
  22. Liu, Jun & Fu, Hongfei & Zhang, Jiansong, 2020. "A QSC method for fractional subdiffusion equations with fractional boundary conditions and its application in parameters identification," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 174(C), pages 153-174.
  23. Pu-yan Nie, 2014. "Penalty mechanism design," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 417-429, December.
  24. S. Đorđević, Snežana, 2016. "A note on a multiplicative parameters gradient method," Applied Mathematics and Computation, Elsevier, vol. 283(C), pages 90-107.
  25. Guang Li & Paat Rusmevichientong & Huseyin Topaloglu, 2015. "The d -Level Nested Logit Model: Assortment and Price Optimization Problems," Operations Research, INFORMS, vol. 63(2), pages 325-342, April.
  26. Saman Babaie-Kafaki & Reza Ghanbari, 2017. "A class of adaptive Dai–Liao conjugate gradient methods based on the scaled memoryless BFGS update," 4OR, Springer, vol. 15(1), pages 85-92, March.
  27. Fahimeh Biglari & Ali Ebadian, 2015. "Limited memory BFGS method based on a high-order tensor model," Computational Optimization and Applications, Springer, vol. 60(2), pages 413-422, March.
  28. Min Xi & Wenyu Sun & Yannan Chen & Hailin Sun, 2020. "A derivative-free algorithm for spherically constrained optimization," Journal of Global Optimization, Springer, vol. 76(4), pages 841-861, April.
  29. Sergio González-Andrade, 2017. "A preconditioned descent algorithm for variational inequalities of the second kind involving the p-Laplacian operator," Computational Optimization and Applications, Springer, vol. 66(1), pages 123-162, January.
  30. Bilian Chen & Zhening Li & Shuzhong Zhang, 2015. "On optimal low rank Tucker approximation for tensors: the case for an adjustable core size," Journal of Global Optimization, Springer, vol. 62(4), pages 811-832, August.
  31. Costa, Carina Moreira & Grapiglia, Geovani Nunes, 2020. "A subspace version of the Wang–Yuan Augmented Lagrangian-Trust Region method for equality constrained optimization," Applied Mathematics and Computation, Elsevier, vol. 387(C).
  32. Zheng, Sanpeng & Feng, Renzhong, 2023. "A variable projection method for the general radial basis function neural network," Applied Mathematics and Computation, Elsevier, vol. 451(C).
  33. Wenyu Sun & Chengjin Li & Raimundo Sampaio, 2011. "On duality theory for non-convex semidefinite programming," Annals of Operations Research, Springer, vol. 186(1), pages 331-343, June.
  34. Na Huang, 2022. "On R-linear convergence analysis for a class of gradient methods," Computational Optimization and Applications, Springer, vol. 81(1), pages 161-177, January.
  35. Jinyan Fan & Jianyu Pan, 2011. "An improved trust region algorithm for nonlinear equations," Computational Optimization and Applications, Springer, vol. 48(1), pages 59-70, January.
  36. XiaoLiang Dong & Hongwei Liu & Yubo He, 2015. "A Self-Adjusting Conjugate Gradient Method with Sufficient Descent Condition and Conjugacy Condition," Journal of Optimization Theory and Applications, Springer, vol. 165(1), pages 225-241, April.
  37. Dan Xue & Wenyu Sun & Liqun Qi, 2014. "An alternating structured trust region algorithm for separable optimization problems with nonconvex constraints," Computational Optimization and Applications, Springer, vol. 57(2), pages 365-386, March.
  38. Zhen-Yuan Ji & Yu-Hong Dai, 2023. "Greedy PSB methods with explicit superlinear convergence," Computational Optimization and Applications, Springer, vol. 85(3), pages 753-786, July.
  39. Zohre Aminifard & Saman Babaie-Kafaki, 2019. "An optimal parameter choice for the Dai–Liao family of conjugate gradient methods by avoiding a direction of the maximum magnification by the search direction matrix," 4OR, Springer, vol. 17(3), pages 317-330, September.
  40. Hai-Jun Wang & Qin Ni, 2010. "A Convex Approximation Method For Large Scale Linear Inequality Constrained Minimization," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 27(01), pages 85-101.
  41. Shummin Nakayama & Yasushi Narushima & Hiroshi Yabe, 2021. "Inexact proximal memoryless quasi-Newton methods based on the Broyden family for minimizing composite functions," Computational Optimization and Applications, Springer, vol. 79(1), pages 127-154, May.
  42. Jianjun Liu & Xiangmin Xu & Xuehui Cui, 2018. "An accelerated nonmonotone trust region method with adaptive trust region for unconstrained optimization," Computational Optimization and Applications, Springer, vol. 69(1), pages 77-97, January.
  43. Liu, Jianjun & Zhai, Rui & Liu, Yuhan & Li, Wenliang & Wang, Bingzhe & Huang, Liyuan, 2021. "A quasi fractional order gradient descent method with adaptive stepsize and its application in system identification," Applied Mathematics and Computation, Elsevier, vol. 393(C).
  44. Hamid Esmaeili & Morteza Kimiaei, 2016. "A trust-region method with improved adaptive radius for systems of nonlinear equations," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 83(1), pages 109-125, February.
  45. Yutao Zheng & Bing Zheng, 2017. "Two New Dai–Liao-Type Conjugate Gradient Methods for Unconstrained Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 175(2), pages 502-509, November.
  46. Geovani N. Grapiglia & Ekkehard W. Sachs, 2017. "On the worst-case evaluation complexity of non-monotone line search algorithms," Computational Optimization and Applications, Springer, vol. 68(3), pages 555-577, December.
  47. Vladimir Rakočević & Milena J. Petrović, 2022. "Comparative Analysis of Accelerated Models for Solving Unconstrained Optimization Problems with Application of Khan’s Hybrid Rule," Mathematics, MDPI, vol. 10(23), pages 1-13, November.
  48. Johannes Brust & Jennifer B. Erway & Roummel F. Marcia, 2017. "On solving L-SR1 trust-region subproblems," Computational Optimization and Applications, Springer, vol. 66(2), pages 245-266, March.
  49. Waziri, Mohammed Yusuf & Ahmed, Kabiru & Sabi’u, Jamilu, 2019. "A family of Hager–Zhang conjugate gradient methods for system of monotone nonlinear equations," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 645-660.
  50. F. Aragón Artacho & A. Belyakov & A. Dontchev & M. López, 2014. "Local convergence of quasi-Newton methods under metric regularity," Computational Optimization and Applications, Springer, vol. 58(1), pages 225-247, May.
  51. Najib Ullah & Abdullah Shah & Jamilu Sabi’u & Xiangmin Jiao & Aliyu Muhammed Awwal & Nuttapol Pakkaranang & Said Karim Shah & Bancha Panyanak, 2023. "A One-Parameter Memoryless DFP Algorithm for Solving System of Monotone Nonlinear Equations with Application in Image Processing," Mathematics, MDPI, vol. 11(5), pages 1-26, March.
  52. Tobias Rösch & Peter Treffinger, 2019. "Cluster Analysis of Distribution Grids in Baden-Württemberg," Energies, MDPI, vol. 12(20), pages 1-25, October.
  53. Xiaojing Zhu & Hiroyuki Sato, 2020. "Riemannian conjugate gradient methods with inverse retraction," Computational Optimization and Applications, Springer, vol. 77(3), pages 779-810, December.
  54. Hamid Esmaeili & Morteza Kimiaei, 2016. "A trust-region method with improved adaptive radius for systems of nonlinear equations," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 83(1), pages 109-125, February.
  55. Lijuan Zhao & Wenyu Sun, 2013. "A Conic Affine Scaling Dogleg Method For Nonlinear Optimization With Bound Constraints," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(03), pages 1-30.
  56. Chen, Wang & Yang, Xinmin & Zhao, Yong, 2023. "Memory gradient method for multiobjective optimization," Applied Mathematics and Computation, Elsevier, vol. 443(C).
  57. Jodi Kraus & Ryan W. Russell & Elena Kudryashova & Chaoyi Xu & Nidhi Katyal & Juan R. Perilla & Dmitri S. Kudryashov & Tatyana Polenova, 2022. "Magic angle spinning NMR structure of human cofilin-2 assembled on actin filaments reveals isoform-specific conformation and binding mode," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  58. Simone Görner & Christian Kanzow, 2016. "On Newton’s Method for the Fermat–Weber Location Problem," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 107-118, July.
  59. Chengjin Li, 2014. "A New Approximation of the Matrix Rank Function and Its Application to Matrix Rank Minimization," Journal of Optimization Theory and Applications, Springer, vol. 163(2), pages 569-594, November.
  60. Saman Babaie-Kafaki & Reza Ghanbari, 2016. "Descent Symmetrization of the Dai–Liao Conjugate Gradient Method," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(02), pages 1-10, April.
  61. Benjamin Lev, 2007. "Book Reviews," Interfaces, INFORMS, vol. 37(2), pages 197-204, April.
  62. Chen, Liang, 2016. "A high-order modified Levenberg–Marquardt method for systems of nonlinear equations with fourth-order convergence," Applied Mathematics and Computation, Elsevier, vol. 285(C), pages 79-93.
  63. Xin-Wei Liu & Yu-Hong Dai & Ya-Kui Huang, 2022. "A primal-dual interior-point relaxation method with global and rapidly local convergence for nonlinear programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 96(3), pages 351-382, December.
  64. Yasushi Narushima & Shummin Nakayama & Masashi Takemura & Hiroshi Yabe, 2023. "Memoryless Quasi-Newton Methods Based on the Spectral-Scaling Broyden Family for Riemannian Optimization," Journal of Optimization Theory and Applications, Springer, vol. 197(2), pages 639-664, May.
  65. Yeerjiang Halimu & Chao Zhou & Qi You & Jun Sun, 2022. "A Quantum-Behaved Particle Swarm Optimization Algorithm on Riemannian Manifolds," Mathematics, MDPI, vol. 10(22), pages 1-20, November.
  66. Amaro, Jordan & Mendiburu, Andrés Z. & Ávila, Ivonete, 2018. "Modeling of syngas composition obtained from fluidized bed gasifiers using Kuhn–Tucker multipliers," Energy, Elsevier, vol. 152(C), pages 371-382.
  67. Mostafa Shibl & Loay Ismail & Ahmed Massoud, 2020. "Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers," Energies, MDPI, vol. 13(20), pages 1-24, October.
  68. N. Eslami & B. Najafi & S. M. Vaezpour, 2023. "A Trust Region Method for Solving Multicriteria Optimization Problems on Riemannian Manifolds," Journal of Optimization Theory and Applications, Springer, vol. 196(1), pages 212-239, January.
  69. Saman Babaie-Kafaki, 2012. "A note on the global convergence theorem of the scaled conjugate gradient algorithms proposed by Andrei," Computational Optimization and Applications, Springer, vol. 52(2), pages 409-414, June.
  70. Ji, Li-Qun, 2015. "An assessment of agricultural residue resources for liquid biofuel production in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 561-575.
  71. Babaie-Kafaki, Saman & Ghanbari, Reza, 2014. "The Dai–Liao nonlinear conjugate gradient method with optimal parameter choices," European Journal of Operational Research, Elsevier, vol. 234(3), pages 625-630.
  72. Saman Babaie-Kafaki, 2015. "On Optimality of the Parameters of Self-Scaling Memoryless Quasi-Newton Updating Formulae," Journal of Optimization Theory and Applications, Springer, vol. 167(1), pages 91-101, October.
  73. Songqiang Qiu, 2019. "Convergence of a stabilized SQP method for equality constrained optimization," Computational Optimization and Applications, Springer, vol. 73(3), pages 957-996, July.
  74. Jifeng Bao & Carisa Kwok Wai Yu & Jinhua Wang & Yaohua Hu & Jen-Chih Yao, 2019. "Modified inexact Levenberg–Marquardt methods for solving nonlinear least squares problems," Computational Optimization and Applications, Springer, vol. 74(2), pages 547-582, November.
  75. Chunfeng Cui & Qingna Li & Liqun Qi & Hong Yan, 2018. "A quadratic penalty method for hypergraph matching," Journal of Global Optimization, Springer, vol. 70(1), pages 237-259, January.
  76. Marko Miladinović & Predrag Stanimirović & Sladjana Miljković, 2011. "Scalar Correction Method for Solving Large Scale Unconstrained Minimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 151(2), pages 304-320, November.
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