Dependent-chance programming with fuzzy decisions

被引：108

作者：

Liu, BD ^{[1
]}

机构：

[1] Tsing Hua Univ, Dept Math Sci, Beijing 100084, Peoples R China

来源：

IEEE TRANSACTIONS ON FUZZY SYSTEMS | 1999年 / 7卷 / 03期

基金：

中国国家自然科学基金;

关键词：

fuzzy decision; fuzzy programming; fuzzy simulation; genetic algorithm;

D O I：

10.1109/91.771090

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Dependent-chance programming (DCP) is a new type of stochastic programming and has been extended to the area of fuzzy programming, This paper provides a spectrum of DCP and dependent-chance multiobjective programming (DCMOP) as Hell as dependent-chance goal programming (DCGP) models with fuzzy rather than crisp decisions. The terms of uncertain environment, event, chance function, and induced constraints are discussed in the case of fuzzy decisions. A technique of fuzzy simulation is also designed for computing chance functions. Finally, we present a fuzzy simulation-based genetic algorithm For solving these models and illustrate its effectiveness by some numerical examples.

引用

页码：354 / 360

页数：7

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