Soto, R.Crawford, B.Galleguillos, C.Barraza J.Lizama S.Muñoz A.Vilches J.Misra, S.Paredes, F.6/22/20222022-06-226/22/20222022-06-222015https://doi.org/10.1007/978-3-319-21404-7_14The set covering problem is a classical model in the subject of combinatorial optimization for service allocation, that consists in finding a set of solutions for covering a range of needs at the lowest possible cost. In this paper, we report various approximate methods to solve this problem, such as Cuckoo Search, Bee Colony, Firefly Optimization, and Electromagnetism-Like Algorithms. We illustrate experimental results of these metaheuristics for solving a set of 65 non-unicost set covering problems from the Beasley’s OR-Library. © Springer International Publishing Switzerland 2015.application/pdfen-USinfo:eu-repo/semantics/closedAccessComputer ScienceMathematicsinfo:eu-repo/semantics/conferenceObject10.1007/978-3-319-21404-7_14http://purl.org/pe-repo/ocde/ford#2.02.04