Abstract
The multiobjective set covering problem (MOSCP), a challenging combinatorial optimization problem, has received limited attention in the literature. This paper presents a heuristic algorithm to approximate the Pareto set of the MOSCP. The proposed algorithm applies a local branching approach on a tree structure and is enhanced with a node exploration strategy specially developed for the MOSCP. The main idea is to partition the search region into smaller subregions based on the neighbors of a reference solution and then to explore each subregion for the Pareto points of the MOSCP. Numerical experiments for instances with two, three and four objectives set covering problems are reported. Results on a performance comparison with benchmark algorithms from the literature are also included and show that the new algorithm is competitive and performs best on some instances.
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The support from the Scientific and Technological Research Council of Turkey (TUBITAK) for B. Soylu, who was a visiting assistant professor for a year at the Department of Mathematical Sciences, Clemson University, Clemson, SC, when working on this paper, is gratefully acknowledged.
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Weerasena, L., Wiecek, M.M. & Soylu, B. An algorithm for approximating the Pareto set of the multiobjective set covering problem. Ann Oper Res 248, 493–514 (2017). https://doi.org/10.1007/s10479-016-2229-x
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DOI: https://doi.org/10.1007/s10479-016-2229-x