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A Filter-and-Fan Metaheuristic for the 0-1 Multidimensional Knapsack Problem

Mahdi Khemakhem, Boukthir Haddar, Khalil Chebil, Saïd Hanafi

Source Title: International Journal of Applied Metaheuristic Computing (IJAMC)3(4)

ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781466610866|DOI: 10.4018/jamc.2012100103

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MLA

Khemakhem, Mahdi, et al. "A Filter-and-Fan Metaheuristic for the 0-1 Multidimensional Knapsack Problem." IJAMC vol.3, no.4 2012: pp.43-63. http://doi.org/10.4018/jamc.2012100103

APA

Khemakhem, M., Haddar, B., Chebil, K., & Hanafi, S. (2012). A Filter-and-Fan Metaheuristic for the 0-1 Multidimensional Knapsack Problem. International Journal of Applied Metaheuristic Computing (IJAMC), 3(4), 43-63. http://doi.org/10.4018/jamc.2012100103

Chicago

Khemakhem, Mahdi, et al. "A Filter-and-Fan Metaheuristic for the 0-1 Multidimensional Knapsack Problem," International Journal of Applied Metaheuristic Computing (IJAMC) 3, no.4: 43-63. http://doi.org/10.4018/jamc.2012100103

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Abstract

This paper proposes a new hybrid tree search algorithm to the Multidimensional Knapsack Problem (MKP) that effectively combines tabu search with a dynamic and adaptive neighborhood search procedure. The authors’ heuristic, based on a filter-and-fan (F&F) procedure, uses a Linear Programming-based Heuristic to generate a starting solution to the F&F process. A tabu search procedure is used to try to enhance the best solution value provided by the F&F method that generates compound moves by a strategically truncated form of tree search. They report the first application of the F&F method to the MKP. 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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A Filter-and-Fan Metaheuristic for the 0-1 Multidimensional Knapsack Problem

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