Soto, RicardoCrawford, BroderickGalleguillos, CristianBarraza, JorgeLizama, SebastianMunoz, AlexisParedes, Fernando2024-07-052024-07-0520156978331921404797833192140300302-97431611-334910.1007/978-3-319-21404-7_142-s2.0-84948971651https://doi.org/10.1007/978-3-319-21404-7_14https://hdl.handle.net/20.500.14411/752Misra, Sanjay/0000-0002-3556-9331; Galleguillos, Cristian/0000-0001-9460-8719; Crawford, Broderick/0000-0001-5500-0188The 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.eninfo:eu-repo/semantics/closedAccessCombinatorial optimizationSet covering problemCuckoo search algorithmBee colony algorithmFirefly optimization algorithmElectromagnetism-Like algorithmConference Object9155187202WOS:000364988700014