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Communication Dans Un Congrès Année : 2020

A Two-Stage epsilon-Constraint Strategy-Based Heuristic for Bi-Objective Quadratic Multiple Knapsack Problems

Résumé

In this paper, we propose a two-stage method for solving the Bi-Objective Quadratic Multiple Knapsack Problem (BO-QMKP). The method combines both a special local branching (the first stage) and the epsilon-constraint (the second stage) strategies, where the local branching tries to intensify the search process while a series of epsilon-constraints are added to tailor a diversification of the search space. The method is based on solving a series of mono-objective optimization problems: from the current problem, provided by combining the original problem and an epsilon-constraint (using a single objective function). an optimization phase is applied in order to generate a set of non-dominated solutions. A preliminary experimental part is given, where the performance of the proposed two-stage method is evaluated on a set of benchmark containing large-scale instances. Its provided results are compared to those achieved by one of the best method available in the literature. Encouraging results have been obtained.
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Dates et versions

hal-03617886 , version 1 (23-03-2022)

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  • HAL Id : hal-03617886 , version 1

Citer

Meziane Aider, Oussama Gacem, Mhand Hifi. A Two-Stage epsilon-Constraint Strategy-Based Heuristic for Bi-Objective Quadratic Multiple Knapsack Problems. 2020 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2020), Nov 2020, Stockholm, Sweden. pp.51-55. ⟨hal-03617886⟩

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