Harnessing memetic algorithms: a practical guide

Carlos Cotta ()
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Carlos Cotta: Universidad de Málaga

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2025, vol. 33, issue 2, No 6, 327-356

Abstract: 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.

Keywords: Memetic algorithms; Evolutionary computation; Local search; GRASP; Aircraft landing scheduling; 68T05; 68T20; 68W50 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11750-024-00694-8

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