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2018 | OriginalPaper | Chapter

15. Genetic Algorithms

Authors: Carlos García-Martínez, Francisco J. Rodriguez, Manuel Lozano

Published in: Handbook of Heuristics

Publisher: Springer International Publishing

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Abstract

This chapter presents the fundamental concepts of genetic algorithms (GAs) that have become an essential tool for solving optimization problems in a wide variety of fields. The first part of this chapter is devoted to the revision of the basic components for the design of GAs. We illustrate this construction process through its application for solving three widely known optimization problems as knapsack problem, traveling salesman problem, and real-parameter optimization. The second part of the chapter focuses on the study of diversification techniques that represent a fundamental issue in order to achieve an effective search in GAs. In fact, analyzing its diversity has led to the presentation of numerous GA models in the literature. Similarly, the hybridization with other metaheuristics and optimization methods has become a very fruitful research area. The third part of the chapter is dedicated to the study of these hybrid methods. In closing, in the fourth part, we outline the wide spectrum of application areas that shows the level of maturity and the wide research community of the GA field.
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Metadata
Title
Genetic Algorithms
Authors
Carlos García-Martínez
Francisco J. Rodriguez
Manuel Lozano
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-07124-4_28

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