A Hybrid Intelligent Algorithm for Stochastic Multilevel Programming
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概要
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In this paper, a decentralized decision-making problem in stochastic environment is formulated as expected value multilevel programming, and chance-constrained multilevel programming according to different decision criteria. In order to solve the proposed stochastic multilevel programming models for finding the Stackelberg-Nash equilibrium, genetic algorithm, neural network and stochastic simulation are integrated to produce a hybrid intelligent algorithm. Finally, two numerical examples are provided to illustrate the effectiveness of the hybrid intelligent algorithm.
- 2004-10-01
著者
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Gen Mitsuo
Graduate School of Engineering Ashikaga Institute of Technology
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Liu Baoding
Uncertainty Theory Laboratory Department Of Mathematical Sciences Tsinghua University
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Gen Mitsuo
Graduate School Of Information Production And Systems Waseda University
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Gao J
Xi'an Jiaotong Univ. China
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GAO Jinwu
Uncertainty Theory Laboratory, Department of Mathematical Sciences, Tsinghua University
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