Connectedness and Local Search for Bicriteria Knapsack Problems
Authors
Abstract
This article reports an experimental study on a given structural property of connectedness of optimal solutions for two variants of the bicriteria knapsack problem. A local search algorithm that exploresthis property is then proposed and its performance is compared against exact algorithms in terms of running time and number of optimal solutions found. The experimental results indicate that this simple
local search algorithm is able to find a representative set of optimal solutions in most of the cases, and in much less time than exact approaches.
Conference
11th European Conference on Evolutionary Computation in Combinatorial Optimisation, LNCS 6622, 48-59, Springer, April 2011Cited by
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Information Sciences, 2015
RLV Moritz
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Year 2014 : 2 citations
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Enguerran Grandchamp, Evelin Fonseca-Cruz, A Two-Phase Multiobjective Local Search for GIS Information Fusion: Spatial Homogeneity and Semantic Information Tradeoff, Information Fusion and Geographic Information Systems (IF AND GIS 2013), Lecture Notes in Geoinformation and Cartography 2014, pp 149-165
Year 2013 : 1 citations
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J. Gorski, K. Klamroth, S. Ruzika, Connectedness of Efficient Solutions in Multiple Objective Combinatorial Optimization, Journal of Optimization Theory and Applications, 150, 3, 475-497, 2011.