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Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17

C. H. Dagli
C. H. Dagli
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ASME Press
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In this paper, we propose an effective evolutionary algorithm for solving the capacitated minimum spanning tree problem in dynamic environment. The purpose is to improve Quality of Service (QoS) of Next Generation Network (NGN) with considering the network provisioning capability and dynamic environment. We formulate this problem with minimizing the communication cost (as a kind of performance measures for NGN's QoS). As we known, this kind of models is NP-complete. We investigate the different encoding, crossover and mutation operators on the performance of EAs to design of MST problems. Based on the performance analysis of these encoding methods in EAs, we improve predecessor-based encoding, in which initialization depends on an underlying random spanning-tree algorithm. Numerical experiments with various scales of communication network problems show the effectiveness and the efficiency of our approach by comparing with the recent researches.

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