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Dependent-chance programming: A class of stochastic optimization

✍ Scribed by Baoding Liu

Publisher: Elsevier Science
Year: 1997
Tongue: English
Weight: 993 KB
Volume: 34
Category: Article
ISSN: 0898-1221
DOI: 10.1016/s0898-1221(97)00237-x

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✦ Synopsis

This paper provides a theoretical framework of dependent-chance programming, as well as dependent-chance multiobjective programming and dependent-chance goal programming which are new types of stochastic optimization. A stochastic simulation based genetic algorithm is also designed for solving dependent-chance programming models.

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