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Fuzzy Random Dependent-Chance Bilevel Programming with Applications

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Advances in Neural Networks – ISNN 2007 (ISNN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4492))

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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.

This work was supported by National Natural Science Foundation of China (No.70601034) and Research Foundation of Renmin University of China.

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Author information

Authors and Affiliations

  1. Economy,Industry and Business Management College, Chongqing University, Chongqing 400044, China

    Rui Liang

  2. School of Information, Renmin University of China, Beijing 100872, China

    Jinwu Gao

  3. Department of Mathematics, Josai University, Sakado, Saitama 350-0248, Japan

    Kakuzo Iwamura

Authors
  1. Rui Liang
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  2. Jinwu Gao
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  3. Kakuzo Iwamura
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Editor information

Derong Liu Shumin Fei Zengguang Hou Huaguang Zhang Changyin Sun

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Liang, R., Gao, J., Iwamura, K. (2007). Fuzzy Random Dependent-Chance Bilevel Programming with Applications . In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_32

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  • DOI: https://doi.org/10.1007/978-3-540-72393-6_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72392-9

  • Online ISBN: 978-3-540-72393-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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