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Adaptive Memory Algorithm with the Covering Recombination Operator

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Published in Dinh, T.-P. & Nguyen, N.-T. & Le Thi, H.-A. Proceedings of the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2015 - Part II. Metz (France) - 11-13 May 2015 - Piscataway: Springer. 2015, p. 153-164
Collection Advances in Intelligent Systems and Computing; 360
Abstract The adaptive memory algorithm (AMA) is a population-based metaheuristics initially developed in 1995 by Rochat and Taillard. AMA relies on a central memory M and consists in three steps: generate a new solution s from M with a recombination operator, improve s with a local search operator, and use s to update M with a memory update operator. In 1999, Galinier and Hao proposed the GPX recombination operator for the graph coloring problem. In this paper, AMC, a general type of evolutionary algorithm, is formalized and called Adaptive Memory Algorithm with the Covering Recombination Operator. It relies on a specific formulation of the considered problem and on a generalization of the GPX recombination operator. It will be showed that AMC has obtained promising results in various domains, such as graph coloring, satellite range scheduling and project management.
Keywords Evolutionary algorithmsPopulation-based metaheuristics
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ISBN: 978-3-319-18166-0
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ZUFFEREY, Nicolas. Adaptive Memory Algorithm with the Covering Recombination Operator. In: Dinh, T.-P. & Nguyen, N.-T. & Le Thi, H.-A. (Ed.). Proceedings of the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2015 - Part II. Metz (France). Piscataway : Springer, 2015. p. 153-164. (Advances in Intelligent Systems and Computing; 360) https://archive-ouverte.unige.ch/unige:73314

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Deposited on : 2015-06-23

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