运筹学

一类带有MaxEMin评判的补偿型随机规划算法

展开
  • 1. 华北电力大学数理系, 河北保定 071003

收稿日期: 2016-04-19

  网络出版日期: 2016-12-15

基金资助

国家自然科学基金(No. 51576066)

A class recourse  stochastic programs algorithm with MaxEMin evaluation

Expand
  • 1. Department of Mathematics and Physics, North China Electric Power University, Baoding 071003, Hebei, China

Received date: 2016-04-19

  Online published: 2016-12-15

摘要

补偿型随机规划一般假定随机变量的概率分布具有完备信息, 但实际情况往往只能获得部分信息. 针对离散概率具有一类线性部分信息条件而建立了带有MaxEMin评判的两阶段随机规划模型, 借助二次规划和对偶分解方法得到了可行性切割和最优切割, 给出了基于L-型的求解算法, 并证明了算法的收敛性. 通过数值实验表明了算法的有效性.

本文引用格式

张艳丽, 马新顺 . 一类带有MaxEMin评判的补偿型随机规划算法[J]. 运筹学学报, 2016 , 20(4) : 52 -60 . DOI: 10.15960/j.cnki.issn.1007-6093.2016.04.006

Abstract

The recourse-based stochastic programming generally assumes that the probability distribution of the random variables has complete information, but the actual situation is that we often get only part of the information. In this paper, we establish a two-stage stochastic programming model with MaxEMin evaluation under linear partial information of discrete probability distribution. We use quadratic programming and the dual decomposition method to get the feasible and optimal cuttings, then give an algorithm based on the L-shaped method. Finally, a numerical example shows the effectiveness of the proposed algorithm.

参考文献

[1] Dantzig G B, Ferguson A. The allocation of air craft routes-an example of linear programming under uncertainty [J]. Management Science, 1956, 3: 23-34.
[2] Walkup D W, Wets R J B. Stochastic programs with recourse [J]. SIAM Journal on Applied Mathematics, 1967, 15(5): 1299-1314.
[3] Birge J R, Louveaux F. Introduction to Stochastic Programming [M]. New York: Springer-Verlag, 2003.
[4] Slyke R M V, Wets R. L-shaped linear programs with applications to optimal control and stochastic programming [J]. SIAM Journal on Applied Mathematics, 1969, 17(4): 638-663.
[5] Evtushenko Y G, Golikov A I, Mollaverdy N. Augmented Lagrangian method for large-scale linear programming problems [J]. Optimization Methods and Software, 2005, 20: 515–524.
[6] Ketabchi S, Kahoo M B. Augmented Lagrangian method within L-shape method for stochastic linear programs [J]. Applied Mathematics and Computation, 2015, 266: 12-20.
[7] Abdelaziz F B, Masri H. Stochastic programming with fuzzy linear partial information on probability distribution [J]. European Journal of Operational Research, 2005, 162: 619-629.
[8] Abdelaziz F B, Masri H. Multistage stochastic programming with fuzzy probability distribution [J].  Fuzzy Sets and Systems, 2009, 160: 3239-3249.
[9] Kofler E. Linear partial information with applications [J].  Fuzzy Sets and Systems, 2001, 118: 167-177.
[10] Chen X J, Qi L Q, Womersley R S. Newton's method for quadratic stochastic programs with recourse [J].  Journal of Computational and Applied Mathematics, 1995, 60: 29-46.
[11] Boyd S, Vandenberghe L. Convex Optimization [M]. Cambridge: Cambridge University Press, 2004.
[12] 袁亚湘, 孙文瑜. 最优化理论与方法  [M]. 北京:科学出版社, 2008.
文章导航

/