Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

Abstract

Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout… (More)
DOI: 10.1155/2014/154676

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Cite this paper

@inproceedings{Osaba2014CrossoverVM, title={Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems}, author={Eneko Osaba and Roberto Carballedo and F. Diaz and Enrique Onieva and I. de la Iglesia and Asier Perallos}, booktitle={TheScientificWorldJournal}, year={2014} }