A genetic algorithm based approach for the uncapacitated continuous location–allocation problem

A genetic algorithm based approach for the uncapacitated continuous location–allocation problem

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Article ID: iaor20042499
Country: Netherlands
Volume: 123
Issue: 1
Start Page Number: 203
End Page Number: 222
Publication Date: Oct 2003
Journal: Annals of Operations Research
Authors: ,
Keywords: genetic algorithms
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.

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