Genetic Algorithms

Carlos García-Martínez (), Francisco J. Rodriguez () and Manuel Lozano ()
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Carlos García-Martínez: University of Córdoba, Department of Computing and Numerical Analysis
Francisco J. Rodriguez: University of Granada, Department of Computer Science and Artificial Intelligence
Manuel Lozano: University of Granada, Department of Computer Science and Artificial Intelligence

Chapter 15 in Handbook of Heuristics, 2018, pp 431-464 from Springer

Abstract: 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.

Keywords: Genetic Algorithms; basic components; GA design; population diversity; diversity maintenance; diversity generation; hybrid genetic algorithms (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-07124-4_28

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DOI: 10.1007/978-3-319-07124-4_28

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