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On the computational efficiency of multiple objective metaheuristics. The knapsack problem case study

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  • Jaszkiewicz, Andrzej

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  • Jaszkiewicz, Andrzej, 2004. "On the computational efficiency of multiple objective metaheuristics. The knapsack problem case study," European Journal of Operational Research, Elsevier, vol. 158(2), pages 418-433, October.
  • Handle: RePEc:eee:ejores:v:158:y:2004:i:2:p:418-433
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    References listed on IDEAS

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    1. Zionts, Stanley, 1981. "A multiple criteria method for choosing among discrete alternatives," European Journal of Operational Research, Elsevier, vol. 7(2), pages 143-147, June.
    2. Pirlot, Marc, 1996. "General local search methods," European Journal of Operational Research, Elsevier, vol. 92(3), pages 493-511, August.
    3. Jaszkiewicz, Andrzej & Slowinski, Roman, 1999. "The `Light Beam Search' approach - an overview of methodology and applications," European Journal of Operational Research, Elsevier, vol. 113(2), pages 300-314, March.
    4. Korhonen, Pekka & Laakso, Jukka, 1986. "Solving generalized goal programming problems using a visual interactive approach," European Journal of Operational Research, Elsevier, vol. 26(3), pages 355-363, September.
    5. Viana, Ana & Pinho de Sousa, Jorge, 2000. "Using metaheuristics in multiobjective resource constrained project scheduling," European Journal of Operational Research, Elsevier, vol. 120(2), pages 359-374, January.
    6. Sun, Minghe & Steuer, Ralph E., 1996. "InterQuad: An interactive quad tree based procedure for solving the discrete alternative multiple criteria problem," European Journal of Operational Research, Elsevier, vol. 89(3), pages 462-472, March.
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    Cited by:

    1. Mavrotas, George & Florios, Kostas, 2013. "An improved version of the augmented epsilon-constraint method (AUGMECON2) for finding the exact Pareto set in Multi-Objective Integer Programming problems," MPRA Paper 105034, University Library of Munich, Germany.
    2. Florios, Kostas & Mavrotas, George & Diakoulaki, Danae, 2010. "Solving multiobjective, multiconstraint knapsack problems using mathematical programming and evolutionary algorithms," European Journal of Operational Research, Elsevier, vol. 203(1), pages 14-21, May.
    3. Rooderkerk, Robert P. & van Heerde, Harald J., 2016. "Robust optimization of the 0–1 knapsack problem: Balancing risk and return in assortment optimization," European Journal of Operational Research, Elsevier, vol. 250(3), pages 842-854.
    4. Ishibuchi, Hisao & Narukawa, Kaname & Tsukamoto, Noritaka & Nojima, Yusuke, 2008. "An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 188(1), pages 57-75, July.
    5. Cerqueus, Audrey & Przybylski, Anthony & Gandibleux, Xavier, 2015. "Surrogate upper bound sets for bi-objective bi-dimensional binary knapsack problems," European Journal of Operational Research, Elsevier, vol. 244(2), pages 417-433.
    6. Bogdan Rębiasz, 2009. "A method for selecting an effective investment project portfolio," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(3), pages 95-117.

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