Next Generation Genetic Algorithms: A User’s Guide and Tutorial

Darrell Whitley ()
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Darrell Whitley: Colorado State University

Chapter Chapter 8 in Handbook of Metaheuristics, 2019, pp 245-274 from Springer

Abstract: Abstract Genetic algorithms are different from most other metaheuristics because they exploit three key ideas: (1) the use of a population of solutions to guide search, (2) the use of crossover operators that recombine two or more solutions to generate new and potentially better solutions, and (3) the active management of diversity to sustain exploration. New ideas that are also introduced in this chapter include (1) the use of deterministic recombination operators that are capable of tunneling between local optima, and (2) the use of deterministic constant time move operators.

Keywords: Steady-state Genetic Algorithm; Partition Crossover; Walsh Coefficients; Recombination Component; Walsh Polynomials (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/978-3-319-91086-4_8

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