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A parameterized shared-memory scheme for parameterized metaheuristics

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Abstract

This paper presents a parameterized shared-memory scheme for parameterized metaheuristics. The use of a parameterized metaheuristic facilitates experimentation with different metaheuristics and hybridation/combinations to adapt them to the particular problem we are working with. Due to the large number of experiments necessary for the metaheuristic selection and tuning, parallelism should be used to reduce the execution time. To obtain parallel versions of the metaheuristics and to adapt them to the characteristics of the parallel system, a unified parameterized shared-memory scheme is developed. Given a particular computational system and fixed parameters for the sequential metaheuristic, the appropriate selection of parameters in the unified parallel scheme eases the development of parallel efficient metaheuristics.

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Authors and Affiliations

  1. Departamento de Estadística, Investigación Operativa y Computación, University of La Laguna, La Laguna, Spain

    Francisco Almeida

  2. Departamento de Informática y Sistemas, University of Murcia, Murcia, Spain

    Domingo Giménez

  3. Centro de Investigación Operativa, University Miguel Hernández, Elche, Spain

    Jose J. López-Espín

Authors
  1. Francisco Almeida
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  2. Domingo Giménez
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  3. Jose J. López-Espín
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Corresponding author

Correspondence to Domingo Giménez.

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Almeida, F., Giménez, D. & López-Espín, J.J. A parameterized shared-memory scheme for parameterized metaheuristics. J Supercomput 58, 292–301 (2011). https://doi.org/10.1007/s11227-011-0585-5

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  • DOI: https://doi.org/10.1007/s11227-011-0585-5

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