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An Efficient Genetic Algorithm for Solving the Multi-Level Uncapacitated Facility Location Problem

In: Computing and Informatics, vol. 29, no. 2
M. Marić

Details:

Year, pages: 2010, 183 - 201
Keywords:
Facility location, genetic algorithms, evolutionary approach
About article:
In this paper a new evolutionary approach for solving the multi-level uncapacitated facility location problem (MLUFLP) is presented. Binary encoding scheme is used with appropriate objective function containing dynamic programming approach for finding sequence of located facilities on each level to satisfy clients' demands. The experiments were carried out on the modified standard single level facility location problem instances. Genetic algorithm (GA) reaches all known optimal solutions for smaller dimension instances, obtained by total enumeration and CPLEX solver. Moreover, all optimal/best known solutions were reached by genetic algorithm for a single-level variant of the problem.
How to cite:
ISO 690:
Marić, M. 2010. An Efficient Genetic Algorithm for Solving the Multi-Level Uncapacitated Facility Location Problem. In Computing and Informatics, vol. 29, no.2, pp. 183-201. 1335-9150.

APA:
Marić, M. (2010). An Efficient Genetic Algorithm for Solving the Multi-Level Uncapacitated Facility Location Problem. Computing and Informatics, 29(2), 183-201. 1335-9150.