Multiple objectives and non-separability in stochastic dynamic programming
作者:
DUAN LI,
期刊:
International Journal of Systems Science
(Taylor Available online 1990)
卷期:
Volume 21,
issue 5
页码: 933-950
ISSN:0020-7721
年代: 1990
DOI:10.1080/00207729008910422
出版商: Taylor & Francis Group
数据来源: Taylor
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.
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