A hybrid quantum particle swarm optimization for the Multidimensional Knapsack Problem. (October 2016)

• Record Type: Journal Article
• Authors: Haddar, Boukthir; Khemakhem, Mahdi; Hanafi, Saïd; Wilbaut, Christophe
• Is Part Of: Engineering applications of artificial intelligence. Volume 55(2016:Jul.)
• Page Start: 1
• Page End: 13
• Publication Date: 2016-10
• Subjects: Combinatorial optimization -- Hybrid heuristic -- Multidimensional Knapsack Problem -- Particle swarm optimization; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2016.05.006
• Languages: English
• ISSNs: 0952-1976

Abstract

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.