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Evolutionary Paradigms

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Handbook of Nature-Inspired and Innovative Computing

Abstract

In recent years, evolutionary computation (EC) techniques have became one of the most popular heuristic search methods successively applied to solve complex research and real-life problems. This chapter presents an overview of the field of EC. Main concepts of biological evolution and some biological paradigms are shown, their influence on EC is discussed, and a general computational scheme currently used in EC is presented. The best recognized classes of EC algorithms are described, such as Evolution Strategies, Genetic Algorithms, Genetic Programming, Evolutionary Programming, and Learning Classifier Systems. However, the main emphasise is on the class of Genetic Algorithms (GAs). Mechanisms of controlling evolutionary process in GAs are discussed, the most known variants of GAs are presented, and current issues of development of GAs are considered.

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  1. Polish-Japanese Institute of Information Technology, Poland

    Franciszek Seredynski

  2. Polish Academy of Sciences, Poland

    Franciszek Seredynski

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  1. The University of Sydney, Australia

    Albert Y. Zomaya

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Seredynski, F. (2006). Evolutionary Paradigms. In: Zomaya, A.Y. (eds) Handbook of Nature-Inspired and Innovative Computing. Springer, Boston, MA. https://doi.org/10.1007/0-387-27705-6_4

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  • DOI: https://doi.org/10.1007/0-387-27705-6_4

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-40532-2

  • Online ISBN: 978-0-387-27705-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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