Journal
NEURAL COMPUTING & APPLICATIONS
Volume 32, Issue 16, Pages 12363-12379Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-020-04832-8
Keywords
Nature-inspired methods; Genetic algorithm; Genetic programming; Differential evolution; Evolution strategy; Evolutionary programming; Real-life applications
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The main focus of this paper is on the family of evolutionary algorithms and their real-life applications. We present the following algorithms: genetic algorithms, genetic programming, differential evolution, evolution strategies, and evolutionary programming. Each technique is presented in the pseudo-code form, which can be used for its easy implementation in any programming language. We present the main properties of each algorithm described in this paper. We also show many state-of-the-art practical applications and modifications of the early evolutionary methods. The open research issues are indicated for the family of evolutionary algorithms.
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