A decomposition method for quadratic zero-one programming
Management Science
Adaptive Memory Tabu Search for Binary Quadratic Programs
Management Science
Tabu Search
Greedy and Local Search Heuristics for Unconstrained Binary Quadratic Programming
Journal of Heuristics
Fast two-flip move evaluations for binary unconstrained quadratic optimisation problems
International Journal of Metaheuristics
Polynomial unconstrained binary optimisation-part 2
International Journal of Metaheuristics
A study of memetic search with multi-parent combination for UBQP
EvoCOP'10 Proceedings of the 10th European conference on Evolutionary Computation in Combinatorial Optimization
A multilevel algorithm for large unconstrained binary quadratic optimization
CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Backbone guided tabu search for solving the UBQP problem
Journal of Heuristics
A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming
Applied Soft Computing
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We provide a method for efficiently evaluating moves that complement values of 0-1 variables in search methods for binary unconstrained quadratic optimisation problems. Our method exploits a compact matrix representation and offers further improvements in speed by exploiting sparse matrices that arise in large-scale applications. The resulting approach, which works with integer or real data, can be applied to improve the efficiency of a variety of different search processes, especially in the case of commonly encountered applications that involve large and sparse matrices. It also enables larger problems to be solved than could previously be handled within a given amount of available memory. Our evaluation method has been embedded in a tabu search algorithm in a sequel to this paper, yielding a method that efficiently matches or improves currently best-known results for instances from widely used benchmark sets having up to 7,000 variables.