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Dependent-Chance Programming Model for Stochastic Network Bottleneck Capacity Expansion Based on Neural Network and Genetic Algorithm

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3612))

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Abstract

This paper considers how to increase the capacities of the elements in a set E efficiently so that probability of the total cost for the increment of capacity can be under an upper limit to maximum extent while the final expansion capacity of a given family F of subsets of E is with a given limit bound. The paper supposes the cost w is a stochastic variable according to some distribution. Network bottleneck capacity expansion problem with stochastic cost is originally formulated as Dependent-chance programming model according to some criteria. For solving the stochastic model efficiently, network bottleneck capacity algorithm, stochastic simulation, neural network(NN) and genetic algorithm(GA) are integrated to produce a hybrid intelligent algorithm. Finally a numerical example is presented.

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Author information

Authors and Affiliations

  1. College of Management, Wuhan University of Technology, Postfach 430077, Wuhan, Hubei, China

    Yun Wu

  2. Department of Computer Sciences, University of Angers, France

    Jian Zhou

  3. College of Management, Huazhong University of Science and Technology, Postfach 430077, Wuhan, Hubei, China

    Yun Wu & Jun Yang

Authors
  1. Yun Wu
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  2. Jian Zhou
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  3. Jun Yang
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Wu, Y., Zhou, J., Yang, J. (2005). Dependent-Chance Programming Model for Stochastic Network Bottleneck Capacity Expansion Based on Neural Network and Genetic Algorithm. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_14

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  • DOI: https://doi.org/10.1007/11539902_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28320-1

  • Online ISBN: 978-3-540-31863-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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