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Parallel Meta-heuristics

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Handbook of Metaheuristics

Abstract

We present a state-of-the-art survey of parallel meta-heuristic strategies, developments, and results. We discuss general design and implementation principles that apply to most meta-heuristic classes and instantiate these principles for neighborhood and population-based meta-heuristics. We also identify a number of trends and promising research directions.

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Acknowledgements

The authors wish to acknowledge the contributions of their colleagues and students, in particular professor Michel Gendreau, Université de Montréal, who collaborated over the years to their work on parallel meta-heuristics for combinatorial optimization. While working on this project, the first author was the NSERC Industrial Research Chair on Logistics Management, ESG UQAM, and adjunct professor with the Department of Computer Science and Operations Research, Université de Montréal, and the Department of Economics and Business Administration, Molde University College, Norway. The second author was adjunct professor with the Department of Computer Science and Operations Research, Université de Montréal, and visiting associate professor with the Department of Computer Science at Oklahoma State University. Partial funding for this project has been provided by the Natural Sciences and Engineering Council of Canada (NSERC), through its Industrial Research Chair and Discovery Grants programs, by the partners of the Chair, CN, Rona, Alimentation Couche-Tard and the Ministry of Transportation of Québec, and by the Fonds québécois de recherche sur la nature et les technologies (FQRNT Québec) through its Team Research grants program.

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Crainic, T.G., Toulouse, M. (2010). Parallel Meta-heuristics. In: Gendreau, M., Potvin, JY. (eds) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol 146. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1665-5_17

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