Fuzzy random dependent-chance bilevel programming with applications

被引：0
|
作者：
Liang, Rui [1 ]
Gao, Jinwu [2 ]
Iwamura, Kakuzo [3 ]
机构：
[1] Chongqing Univ, Econ Ind & Business Management Coll, Chongqing 400044, Peoples R China
[2] Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China
[3] Josai Univ, Dept Math, Saitama 3500248, Japan
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 2, PROCEEDINGS | 2007年 / 4492卷
基金：
中国国家自然科学基金;
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a two-level decentralized decision-making problem is formulated as fuzzy random dependent-chance bilevel programming. Ve define the fuzzy random Nash equilibrium in the lower level problem and the fuzzy random Stackelberg-Nash equilibrium of the overall problem. In order to find the equilibria, we propose a hybrid intelligent algorithm, in which neural network, as uncertain function approximator, plays a crucial role in saving computing time, and genetic algorithm is used for optimization. Finally, we apply the fuzzy random dependent-chance bilevel programming to hierarchical resource allocation problem for illustrating the modelling idea and the effectiveness of the hybrid intelligent algorithm.
引用
收藏
页码：257 / +
页数：3
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