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Genetic Algorithms

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Handbook of Heuristics

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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Authors and Affiliations

  1. Department of Computing and Numerical Analysis, University of Córdoba, Córdoba, Spain

    Carlos García-Martínez

  2. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    Francisco J. Rodriguez & Manuel Lozano

Authors
  1. Carlos García-Martínez
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  2. Francisco J. Rodriguez
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  3. Manuel Lozano
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Correspondence to Carlos García-Martínez .

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Editors and Affiliations

  1. Statistics and Operations Research Department, University of Valencia, Valencia, Spain

    Rafael Martí

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  3. Amazon.com, Inc. and University of Washington, Seattle, Washington, USA

    Mauricio G. C. Resende

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García-Martínez, C., Rodriguez, F.J., Lozano, M. (2018). Genetic Algorithms. In: Martí, R., Pardalos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07124-4_28

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