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Solving multi-stage stochastic mixed integer linear programs by the dual dynamic programming approach

机译:用双重动态规划方法求解多阶段随机混合整数线性规划

摘要

We consider a model of medium-term commodity contracts management. Randomness takes place only in the prices on which the commodities are exchanged, whilst state variable is multi-dimensional, and decision variable is integer. In our previous article, we proposed an algorithm based on the quantization of random process and a dual dynamic programming type approach to solve the continuous relaxation problem. In this paper, we study the multi-stage stochastic mixed integer linear program (SMILP) and show the difficulty when using dual programming type algorithm. We propose an approach based on the cutting plane method combined with the algorithm in our previous article, which gives an upper and a lower bound of the optimal value and a sub-optimal integer solution. Finally, a numerical test on a real problem in energy market is provided.
机译:我们考虑一种中期商品合同管理模型。随机性仅发生在商品交换的价格上,而状态变量是多维的,而决策变量是整数。在之前的文章中,我们提出了一种基于随机过程量化和双重动态规划类型方法的算法,以解决连续松弛问题。在本文中,我们研究了多阶段随机混合整数线性程序(SMILP),并说明了使用双重编程类型算法时的困难。我们在前一篇文章中结合切割算法提出了一种方法,该方法给出了最佳值的上下限和次优整数解。最后,对能源市场中的实际问题进行了数值测试。

著录项

  • 作者

    Cen Zhihao;

  • 作者单位
  • 年度 2012
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  • 原文格式 PDF
  • 正文语种 en
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