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Parallel Strategies for Meta-Heuristics

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Handbook of Metaheuristics

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 57))

Abstract

We present a state-of-the-art survey of parallel meta-heuristic developments and results, discuss general design and implementation principles that apply to most meta-heuristic classes, instantiate these principles for the three meta-heuristic classes currently most extensively used—genetic methods, simulated annealing, and tabu search, and identify a number of trends and promising research directions.

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Authors and Affiliations

  1. Département de management et technologie, Université du Québec à Montréal and Centre de recherche sur les transports Université de Montréal, C.P. 6128, Succursale Centre-ville Montréal (QC), Canada, H3C 3J7

    Teodor Gabriel Crainic

  2. Department of computer science, University of Manitoba, Winnipeg (MB), Canada, R3T2N2

    Michel Toulouse

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  1. Teodor Gabriel Crainic
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  2. Michel Toulouse
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  1. Leeds School of Business, University of Colorado at Boulder, USA

    Fred Glover

  2. College of Business, University of Colorado at Denver, USA

    Gary A. Kochenberger

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Crainic, T.G., Toulouse, M. (2003). Parallel Strategies for Meta-Heuristics. In: Glover, F., Kochenberger, G.A. (eds) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol 57. Springer, Boston, MA. https://doi.org/10.1007/0-306-48056-5_17

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