Algorithms for solving the set coverage problem

Provides an overview of algorithms for solving the set coverage problem. Two alternative formulations of the set coverage problem, which are used by the authors of the algorithms, are considered. A classification of algorithms for solving the set coverage problem is given. The features of the most well-known algorithms for solving the set coverage problem are considered. The main focus is on algorithms using metaheuristics. Among the metaheuristics, there are population-based metaheuristics and single-data-based metaheuristics. Population-based metaheuristics include: swarm-based; based on physics; based on evolution; based on humans. Metaheuristics based on single data: simulated annealing; Taboo search; guided local search; greedy randomized adaptive search procedure.

Authors: P. I. Vaskin, A. A. Liss

Direction: Informatics, Computer Technologies And Control

Keywords: the set coverage problem, the coverage table, the rules for converting coverage tables, methods for solving coverage tables, metaheuristic methods

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