Genetic Algorithms

Colin R. Reeves ()
Additional contact information
Colin R. Reeves: Coventry University

Chapter Chapter 5 in Handbook of Metaheuristics, 2010, pp 109-139 from Springer

Abstract: Abstract Genetic algorithms (GAs) have become popular as a means of solving hard combinatorial optimization problems. The first part of this chapter briefly traces their history, explains the basic concepts and discusses some of their theoretical aspects. It also references a number of sources for further research into their applications. The second part concentrates on the detailed implementation of a GA. It discusses the fundamentals of encoding a ‘genotype’ in different circumstances and describes the mechanics of population selection and management and the choice of genetic ‘operators’ for generating new populations. In closing, some specific guidelines for using GAs in practice are provided.

Keywords: Travel Salesman Problem; Travel Salesman Problem; Crossover Operator; Combinatorial Optimization Problem; Crossover Point (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4419-1665-5_5

Ordering information: This item can be ordered from
http://www.springer.com/9781441916655

DOI: 10.1007/978-1-4419-1665-5_5

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().