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随机规划问题的两种分解算法研究

张 霞1,傅海英2,孙金领3   

  1. 1. 山东科技大学研究生教育学院, 山东 青岛 266510;2. 山东省胶州市第二中学, 山东 胶州 266326;3. 青岛农业大学理学院, 山东 青岛 266109
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-10-24 发布日期:2006-10-24
  • 通讯作者: 张 霞

Two types of decomposition algorithms for stochastic programming

ZHANG Xia1, FU Hai-ying2, SUN Jin-ling3   

  1. 1. Shandong university of Science and Technology, Qingdao 266510, Shandong;2. No.2 Middle School of Shandong, Jiaozhou 266326, Shandong;3. College of Science, Qingdao Agriculture University, Qingdao 266109, Shandong
  • Received:1900-01-01 Revised:1900-01-01 Online:2006-10-24 Published:2006-10-24
  • Contact: ZHANG Xia

摘要: 以二阶段随机规划为例,给出了两种分解算法:基于内点的原始-对偶分解算法和基于Benders分解的算法,此两种算法都是通过将多阶段随机规划中的变量加以分解,生成一系列只含有单变量的规划问题,通过对这些小规模确定性规划问题的求解构造迭代过程,最终收敛到原问题的最优解。

关键词: 随机规划, 原始-对偶分解, Benders分解

Abstract: Based on stochastic programming theory, two types of decomposition algorithms, primal-dual decomposition algorithm and Benders decomposition, were given; both of which can partition the variables into two sets-x and y.Rather than attempting to solve the programming, a collection of smaller sub-problems can be iteratively solved, and a solution to the entire problem was obtained.

Key words: Benders decomposition , primal-dual decomposition, stochastic programming

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  • O221.5
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