Multistart Tabu Search Strategies for the Unconstrained Binary Quadratic Optimization Problem

Gintaras Palubeckis ()

Annals of Operations Research, 2004, vol. 131, issue 1, 259-282

Abstract: This paper describes and experimentally compares five rather different multistart tabu search strategies for the unconstrained binary quadratic optimization problem: a random restart procedure, an application of a deterministic heuristic to specially constructed subproblems, an application of a randomized procedure to the full problem, a constructive procedure using tabu search adaptive memory, and an approach based on solving perturbed problems. In the solution improvement phase a modification of a standard tabu search implementation is used. A computational trick applied to this modification – mapping of the current solution to the zero vector – allowed to significantly reduce the time complexity of the search. Computational results are provided for the 25 largest problem instances from the OR-Library and, in addition, for the 18 randomly generated larger and more dense problems. For 9 instances from the OR-Library new best solutions were found. Copyright Kluwer Academic Publishers 2004

Keywords: binary quadratic optimization; tabu search; multistart strategies; heuristics (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (13)

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DOI: 10.1023/B:ANOR.0000039522.58036.68

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