A Genetic Algorithm Based Approach for the Uncapacitated Continuous Location–Allocation Problem.

Salhi, S. and Gamal, M.D.H. (2003) A Genetic Algorithm Based Approach for the Uncapacitated Continuous Location–Allocation Problem. Annals of Operations Research, 123 (1-4). pp. 203-222. ISSN 0254-5330. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1023/A:1026131531250

Abstract

A GA-based approach is introduced to address the continuous location–allocation problem. Selection and removal procedures based on groups of chromosomes instead of individual chromosomes are put forward and specific crossover and mutation operators that rely on the impact of the genes are proposed. A new operator that injects once in a while new chromosomes into the population is also introduced. This provides diversity within the search and attempts to avoid early convergence. This approach is tested on existing data sets using several runs to evaluate the robustness of the proposed GA approach.

Item Type: Article
Uncontrolled keywords: GA heuristic, location, continuous space
Subjects: H Social Sciences
Divisions: Faculties > Social Sciences > Kent Business School > Management Science
Depositing User: Said Salhi
Date Deposited: 05 Sep 2008 17:10
Last Modified: 14 Jan 2010 14:20
Resource URI: http://kar.kent.ac.uk/id/eprint/5234 (The current URI for this page, for reference purposes)
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