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Harnessing memetic algorithms: a practical guide

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  • Carlos Cotta

    (Universidad de Málaga
    Universidad de Málaga)

Abstract

The aim of this work is to provide a didactic approximation to memetic algorithms (MAs) and how to apply these techniques to an optimization problem. MAs are based on the synergistic combination of ideas from population-based metaheuristics and trajectory-based search/optimization techniques. Most commonly, MAs feature a population-based algorithm as the underlying search engine, endowing it with problem-specific components for exploring the search space, and in particular with local-search mechanisms. In this work, we describe the design of the different elements of the MA to fit the problem under consideration, and go on to perform a detailed case study on a constrained combinatorial optimization problem related to aircraft landing scheduling. An outline of some advanced topics and research directions is also provided.

Suggested Citation

  • Carlos Cotta, 2025. "Harnessing memetic algorithms: a practical guide," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(2), pages 327-356, July.
    • Handle: RePEc:spr:topjnl:v:33:y:2025:i:2:d:10.1007_s11750-024-00694-8
    DOI: 10.1007/s11750-024-00694-8
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