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Memetic and Hybrid Evolutionary Algorithms

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Springer Handbook of Computational Intelligence

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Abstract

This chapter presents an overview of hybridization mechanisms in evolutionary algorithms. Such mechanisms are aimed to introducing problem knowledge in the optimization technique by means of the synergistic combination of general–purpose methods and problemspecific add-ons. This combination is presented in this work from two wide perspectives: memetic algorithms and cooperative optimization models. Memetic algorithms are based on the smart orchestration of global (population-based) and local (trajectorybased) techniques, using an algorithmic scheme in which the latter are often subordinated to the former. As to cooperative models, they are based on the collaboration of different optimization techniques that exchange information in order to boost their respective performances. Both approaches, memetic algorithms and cooperative models, provide a framework to achieve synergistic algorithmic combinations for the resolution of large-scale combinatorial problems.

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Abbreviations

AI:

artificial intelligence

BnB:

branch and bound

CP:

constraint programming

EA:

evolutionary algorithm

EDA:

estimation of distribution algorithm

ER:

edge recombination

LS:

local search

MA:

memetic algorithm

MMA:

multimemetic algorithm

NFL:

no free lunch

OR:

operational research

PMX:

partially-mapped crossover

PSO:

particle swarm optimization

SA:

simulated annealing

TSP:

traveling salesman problem

TS:

tabu search

UCX:

uniform cycle crossover

VNS:

variable neighborhood search

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Authors and Affiliations

  1. Dep. Electronic Engineering, Universidad Nacional Experimental del Táchira, Av. Universidad. Paramillo, San Cristóbal, Venezuela

    Jhon Edgar Amaya

  2. Dep. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Avda Louis Pasteur, 35, 29071, Málaga, Spain

    Carlos Cotta Porras & Antonio J. Fernández Leiva

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    Janusz Kacprzyk

  2. Dep. Electrical and Computer Engineering, University of Alberta, 116 Street 9107, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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Amaya, J.E., Cotta Porras, C., Fernández Leiva, A.J. (2015). Memetic and Hybrid Evolutionary Algorithms. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_52

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  • DOI: https://doi.org/10.1007/978-3-662-43505-2_52

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