Strategic oscillation for the quadratic multiple knapsack problem
Carlos García-Martínez (cgarcia@uco.es),
Fred Glover (glover@opttek.com),
Francisco Rodriguez (fjrodriguez@decsai.ugr.es),
Manuel Lozano (lozano@decsai.ugr.es) and
Rafael Martí (rafael.marti@uv.es)
Computational Optimization and Applications, 2014, vol. 58, issue 1, 185 pages
Abstract:
The quadratic multiple knapsack problem (QMKP) consists in assigning a set of objects, which interact through paired profit values, exclusively to different capacity-constrained knapsacks with the aim of maximising total profit. Its many applications include the assignment of workmen to different tasks when their ability to cooperate may affect the results. Strategic oscillation (SO) is a search strategy that operates in relation to a critical boundary associated with important solution features (such as feasibility). Originally proposed in the context of tabu search, it has become widely applied as an efficient memory-based methodology. We apply strategic oscillation to the quadratic multiple knapsack problem, disclosing that SO effectively exploits domain-specific knowledge, and obtains solutions of particularly high quality compared to those obtained by current state-of-the-art algorithms. Copyright Springer Science+Business Media New York 2014
Keywords: Strategic oscillation; Tabu search; Quadratic multiple knapsack problem; Empirical study (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)
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DOI: 10.1007/s10589-013-9623-y
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