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A hybrid quantum particle swarm optimization for the Multidimensional Knapsack Problem

Abstract : In this paper we propose a new hybrid heuristic approach that combines the Quantum Particle Swarm Optimization technique with a local search method to solve the Multidimensional Knapsack Problem. The approach also incorporates a heuristic repair operator that uses problem-specific knowledge instead of the penalty function technique commonly used for constrained problems. Experimental results obtained on a wide set of benchmark problems clearly demonstrate the competitiveness of the proposed method compared to the state-of-the-art heuristic methods.
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https://hal-uphf.archives-ouvertes.fr/hal-03400781
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Submitted on : Monday, October 25, 2021 - 10:41:21 AM
Last modification on : Wednesday, November 3, 2021 - 5:24:21 AM

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Boukthir Haddar, Mahdi Khemakhem, Said Hanafi, Christophe Wilbaut. A hybrid quantum particle swarm optimization for the Multidimensional Knapsack Problem. Engineering Applications of Artificial Intelligence, Elsevier, 2016, 55, pp.1-13. ⟨10.1016/j.engappai.2016.05.006⟩. ⟨hal-03400781⟩

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