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Network Topology Planning Using MOEA/D with Objective-Guided Operators

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Parallel Problem Solving from Nature - PPSN XII (PPSN 2012)

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Abstract

Multiobjective evolutionary algorithms (MOEAs) have attracted growing attention recently. Problem-specific operators have been successfully used in single objective evolutionary algorithms and it is widely believed that the performance of MOEAs can be improved by using problem-specific knowledge. However, not much work have been done along this direction. Taking a network topology planning problem as an example, we study how to incorporate problem-specific knowledge into the multiobjective evolutionary algorithm based on decomposition (MOEA/D). We propose objective-guided operators for the network topology planning problem and use them in MOEA/D. Experiments are conducted on two test networks and the experimental results show that the MOEA/D algorithm using the proposed operators works very well. The idea in this paper can be generalized to other multiobjective optimization problems.

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Peng, W., Zhang, Q. (2012). Network Topology Planning Using MOEA/D with Objective-Guided Operators. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32964-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-32964-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32963-0

  • Online ISBN: 978-3-642-32964-7

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