W e develop a new local search algorithm for binary optimization problems, whose complexity and performance are explicitly controlled by a parameter Q, measuring the depth of the local search neighborhood. We show that the algorithm is pseudo-polynomial for general cost vector c, and achieves a w 2 / 2w − 1 approximation guarantee for set packing problems with exactly w ones in each column of the constraint matrix A, when using Q = w 2 . Most importantly, we find that the method has practical promise on large…
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