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Article dans une revue

A hybrid population-based algorithm for the bi-objective quadratic multiple knapsack problem

Abstract : 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 (namely 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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https://hal-u-picardie.archives-ouvertes.fr/hal-03617877
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Soumis le : mercredi 23 mars 2022 - 18:07:59
Dernière modification le : jeudi 24 mars 2022 - 03:00:22

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Meziane Aider, Oussama Gacem, Mhand Hifi. A hybrid population-based algorithm for the bi-objective quadratic multiple knapsack problem. Expert Systems With Applications, 2022, 191, ⟨10.1016/j.eswa.2021.116238⟩. ⟨hal-03617877⟩

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