f-Flip strategies for unconstrained binary quadratic programming

Fred Glover () and Jin-Kao Hao ()
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Fred Glover: University of Colorado Leeds School of Business
Jin-Kao Hao: Université d’Angers

Annals of Operations Research, 2016, vol. 238, issue 1, No 28, 657 pages

Abstract: Abstract Unconstrained binary quadratic programming (UBQP) provides a unifying modeling and solution framework for solving a remarkable range of binary optimization problems, including many accompanied by constraints. Current methods for solving UBQP problems customarily rely on neighborhoods consisting of flip moves that select one or more binary variables and “flip” their values to the complementary value (from 1 to 0 or from 0 to 1). We introduce a class of approaches called f-flip strategies that include a fractional value f as one of those available to the binary variables during intermediate stages of solution. A variety of different f-flip strategies, particularly within the context of multi-start algorithms, are proposed for pursuing intensification and diversification goals in metaheuristic algorithms, accompanied by special rules for evaluating and executing f-flips efficiently.

Keywords: 0–1 Optimization; Binary quadratic programming; Metaheuristics; Multi-start algorithms; Computational efficiency (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10479-015-2076-1

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