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Evolutionary Computation

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Evolutionary Computation and Complex Networks

Abstract

Evolutionary algorithms (EAs) are optimization heuristics designed to solve optimization problems. This chapter introduces classical EAs and other advanced methods including differential evolution, memetic algorithms, particle swarm optimization, and multi-objective EAs.

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Notes

  1. 1.

    We will not differentiate between objective and fitness functions in parameter optimization problems in this book.

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Authors and Affiliations

  1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, Shaanxi, China

    Jing Liu

  2. School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia

    Hussein A. Abbass

  3. Department of Computer Science, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong SAR

    Kay Chen Tan

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  1. Jing Liu
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  2. Hussein A. Abbass
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  3. Kay Chen Tan
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Correspondence to Jing Liu .

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Liu, J., Abbass, H.A., Tan, K.C. (2019). Evolutionary Computation. In: Evolutionary Computation and Complex Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-60000-0_1

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