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