Genetic Algorithms

Kumara Sastry, David E. Goldberg and Graham Kendall ()
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Kumara Sastry: University of Illinois
David E. Goldberg: Inc. and University of Illinois
Graham Kendall: University of Nottingham

Chapter Chapter 4 in Search Methodologies, 2014, pp 93-117 from Springer

Abstract: Abstract Genetic algorithms (GAs) are search methods based on principles of natural selection and genetics (Fraser 1957; Bremermann 1958; Holland 1975). We start with a brief introduction of simple GAs and the associated terminologies. GAs encode the decision variables of a search problem into finite-length strings of alphabets of certain cardinality. The strings which are candidate solutions to the search problem are referred to as chromosomes, the alphabets are referred to as genes and the values of genes are called alleles. For example, in a problem such as the traveling salesman problem (TSP), a chromosome represents a route, and a gene may represent a city. In contrast to traditional optimization techniques, GAs work with coding of parameters, rather than the parameters themselves.

Keywords: Genetic Algorithm; Travel Salesman Problem; Travel Salesman Problem; Memetic Algorithm; Search Problem (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-1-4614-6940-7_4

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