Expected Value Model and Algorithm for Network Bottleneck Capacity Expansion Under Fuzzy Environment

  • Yun Wu
  • Zhou Jian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)


This paper considers the capacities of the elements in a set E efficiently so that the total cost for the increment of capacity can be decrease 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 fuzzy variable. Network bottleneck capacity expansion problem with fuzzy cost is originally formulated as Expected value model according to some criteria. For solving the fuzzy model efficiently, network bottleneck capacity algorithm, fuzzy simulation, neural network(NN) and genetic algorithm(GA) are integrated to produce a hybrid intelligent algorithm.


Fuzzy Model Fuzzy Variable Polynomial Algorithm Capacity Expansion Undirected Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yun Wu
    • 1
  • Zhou Jian
    • 2
  1. 1.College of ManagementWuhan University of TechnologyWuhanChina
  2. 2.Department of Computer SciencesUniversity of AngersFrance

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