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Computing Approximate Solutions of the Maximum Covering Problem with GRASP

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Abstract

We consider the maximum covering problem, a combinatorial optimization problem that arises in many facility location problems. In this problem, a potential facility site covers a set of demand points. With each demand point, we associate a nonnegative weight. The task is to select a subset of p > 0 sites from the set of potential facility sites, such that the sum of weights of the covered demand points is maximized. We describe a greedy randomized adaptive search procedure (GRASP) for the maximum covering problem that finds good, though not necessarily optimum, placement configurations. We describe a well-known upper bound on the maximum coverage which can be computed by solving a linear program and show that on large instances, the GRASP can produce facility placements that are nearly optimal.

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Resende, M.G. Computing Approximate Solutions of the Maximum Covering Problem with GRASP. Journal of Heuristics 4, 161–177 (1998). https://doi.org/10.1023/A:1009677613792

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  • DOI: https://doi.org/10.1023/A:1009677613792

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