Fuzzy Random Dependent-Chance Bilevel Programming with Applications

Authors:
Rui Liang;Jinwu Gao;Kakuzo Iwamura
Affiliations:
Economy,Industry and Business Management College, Chongqing University, Chongqing 400044, China;School of Information, Renmin University of China, Beijing 100872, China;Department of Mathematics, Josai University, Sakado, Saitama 350-0248, Japan
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Year:
2007

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Abstract

In this paper, a two-level decentralized decision-making problem is formulated as fuzzy random dependent-chance bilevel programming. We 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.