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Evolutionary Metaheuristics to Solve Multiobjective Assignment Problem in Telecommunication Network: Multiobjective Assignment Problem

Evolutionary Metaheuristics to Solve Multiobjective Assignment Problem in Telecommunication Network: Multiobjective Assignment Problem

Benkanoun Yazid, Bouroubi Sadek, Chaabane Djamal
Copyright: © 2020 |Volume: 11 |Issue: 2 |Pages: 21
ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781799802853|DOI: 10.4018/IJAMC.2020040103
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MLA

Yazid, Benkanoun, et al. "Evolutionary Metaheuristics to Solve Multiobjective Assignment Problem in Telecommunication Network: Multiobjective Assignment Problem." IJAMC vol.11, no.2 2020: pp.56-76. http://doi.org/10.4018/IJAMC.2020040103

APA

Yazid, B., Sadek, B., & Djamal, C. (2020). Evolutionary Metaheuristics to Solve Multiobjective Assignment Problem in Telecommunication Network: Multiobjective Assignment Problem. International Journal of Applied Metaheuristic Computing (IJAMC), 11(2), 56-76. http://doi.org/10.4018/IJAMC.2020040103

Chicago

Yazid, Benkanoun, Bouroubi Sadek, and Chaabane Djamal. "Evolutionary Metaheuristics to Solve Multiobjective Assignment Problem in Telecommunication Network: Multiobjective Assignment Problem," International Journal of Applied Metaheuristic Computing (IJAMC) 11, no.2: 56-76. http://doi.org/10.4018/IJAMC.2020040103

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Abstract

The authors propose a computing approach for solving a multiobjective problem in the telecommunication network field, suggested by an Algerian industrial company. The principal goal is in developing a palliative solution to overcome some generated problems existing in the current management system. A mathematical operational model has been established. The exact algorithms that solve multiobjective optimization problems are not appropriate for large scale problems. However, the application of metaheuristics approach leads perfectly to approximate the Pareto optimal set. In this paper, the authors apply a well-known multiobjective evolutionary algorithm, the Non-dominated Sorting Genetic Algorithm (NSGA-II), compare the obtained results with those generated by the Strength Pareto Evolutionary Algorithm-II (SPEA2) and propose a way to help the decision maker, who is often confronted with the choice of a final solution, to make his preferences afterward using a utility function based on a Choquet integral measure. Finally, numerical experiments are presented to validate the approach.

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