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A Population-Based Algorithm for the Bi-Objective Quadratic Multiple Knapsack Problem

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Résumé

In this paper, the bi-objective quadratic multiple knapsack problem is tackled with a hybrid population-based method. The proposed method starts by computing two reference solutions, where a specialized powerful mono-objective algorithm is used. From both reference solutions, a starting population is built by using a series of perturbations around the solutions. Next, the so-called non-sorting genetic process is combined with a new drop/rebuild operator for generating a series of populations till converging toward an approximate Pareto front with high density. The performance of the Hybrid Population Based Algorithm for the Bi-Objective Quadratic Multiple Knsapsack problem HBPA is evaluated on a set of benchmark instances of the literature containing both medium and large-scale instances. Its provided results are compared to those achieved by the best methods available in the literature. Encouraging results have been obtained.
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Dates et versions

hal-03595221 , version 1 (03-03-2022)

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  • HAL Id : hal-03595221 , version 1

Citer

Méziane Aïder, Oussama Gacem, Mhand Hifi. A Population-Based Algorithm for the Bi-Objective Quadratic Multiple Knapsack Problem. 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, INSA Lyon, Feb 2022, Villeurbanne - Lyon, France. ⟨hal-03595221⟩
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