MULTIPLE OBJECTIVES AND NONSEPARABILITY IN STOCHASTIC DYNAMIC-PROGRAMMING

被引：24
作者：
LI, D
机构：
[1] Department of Systems Engineering, University of Virginia, Charlottes-ville, VA, 22901, Thornton Hall
来源：
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE | 1990年 / 21卷 / 05期
基金：
美国国家科学基金会;
关键词：
D O I：
10.1080/00207729008910422
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A general separable class of stochastic multiobjective optimization problems with perfect state information is considered. A generating approach using a stochastic multiobjective dynamic programming method is developed to find the set of non-inferior solutions. The results reveal the variation of the optimal weighting coefficient vector along a non-inferior trajectory. Non-separability is not an inherent property of dynamic programming. A general class of non-separable dynamic problems can be transformed into corresponding separable multiobjective dynamic programming problems. Multiobjective dynamic programming is shown to be a separation strategy to solve non-separable dynamic programming. © 1990 Taylor & Francis Group, LLC.
引用
收藏
页码：933 / 950
页数：18
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