Dependent-chance programming with fuzzy decisions

被引：107
|
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
收藏
页码：354 / 360
页数：7
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