A Filter-and-Fan Metaheuristic for the 0-1 Multidimensional Knapsack Problem
Mahdi Khemakhem,
Boukthir Haddar,
Khalil Chebil and
Saïd Hanafi
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Mahdi Khemakhem: LOGIQ – ISGI, University of Sfax, Sfax, Tunisia
Boukthir Haddar: LOGIQ – ISGI, University of Sfax, Sfax, Tunisia
Khalil Chebil: LOGIQ – ISGI, University of Sfax, Sfax, Tunisia
Saïd Hanafi: LAMIH, University of Valenciennes, Valenciennes, France
International Journal of Applied Metaheuristic Computing (IJAMC), 2012, vol. 3, issue 4, 43-63
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.
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jamc00:v:3:y:2012:i:4:p:43-63
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