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

Benkanoun Yazid, Bouroubi Sadek and Chaabane Djamal
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Benkanoun Yazid: DGRSDT, USTHB, AMCD-RO Laboratory, BP32 El-Alia, Bab Ezzouar, Algiers, Algeria
Bouroubi Sadek: DGRSDT, USTHB, L'IFORCE Laboratory, BP32 El-Alia, Bab Ezzouar, Algiers, Algeria
Chaabane Djamal: DGRSDT, USTHB, AMCD-RO Laboratory, BP32 El-Alia, Bab Ezzouar, Algiers, Algeria

International Journal of Applied Metaheuristic Computing (IJAMC), 2020, vol. 11, issue 2, 56-76

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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jamc00:v:11:y:2020:i:2:p:56-76

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