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Evolutionary Algorithms — An Overview

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Evolutionary Algorithms in Engineering Applications

Summary

Evolutionary algorithms (EAs), which are based on a powerful principle of evolution: survival of the fittest, and which model some natural phenomena: genetic inheritance and Darwinian strife for survival, constitute an interesting category of modern heuristic search. This introductory article presents the main paradigms of evolutionary algorithms (genetic algorithms, evolution strategies, evolutionary programming, genetic programming) and discusses other (hybrid) methods of evolutionary computation. Also, various constraint-handling techniques in connection with evolutionary algorithms are discussed, since most engineering problems includes some problem-specific constraints.

Evolutionary algorithms have been widely used in science and engineering for solving complex problems. An important goal of research on evolutionary algorithms is to understand the class of problems for which EAs are most suited, and, in particular, the class of problems on which they outperform other search algorithms.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Missouri, St. Louis, MO, 63121, USA

    Dipankar Dasgupta

  2. Department of Computer Science, University of North Carolina, Charlotte, NC, 28223, USA

    Zbigniew Michalewicz

  3. Institute of Computer Science, Polish Academy of Sciences, ul. Ordona 21, 01-237, Warsaw, Poland

    Zbigniew Michalewicz

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  1. Dipankar Dasgupta
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Editors and Affiliations

  1. Mathematical Sciences Department, University of Memphis, Memphis, TN, 38152-6429, USA

    Dipankar Dasgupta

  2. Department of Computer Science, University of North Carolina, 9201 University City Boulevard, Charlotte, NC, 28223-0001, USA

    Zbigniew Michalewicz

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Dasgupta, D., Michalewicz, Z. (1997). Evolutionary Algorithms — An Overview. In: Dasgupta, D., Michalewicz, Z. (eds) Evolutionary Algorithms in Engineering Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03423-1_1

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