A Bi-Objetive Cat Swarm Optimization Algorithm for Set Covering Problem
In this paper, we study a classical problem in combinatorics and computer science, Set Covering Problem. It is one of Karp’s 21 NP-complete problems, using a new and original metaheuristic, Cat Swarm Optimization. This algorithm imitates the domestic cat through two states: seeking and tracing mode. The OR-Library of Beasley instances were used for the benchmark with additional fitness function, thus the problem was transformed from Mono-objective to Bi-objective. The Cat Swarm Optimization finds a set solution non-dominated based on Pareto concepts, and an external file for storing them. The results are promising for further continue in future work optimizing this problem.
KeywordsMultiobjective problems Evolutionary algorithm Swarm optimization Cat swarm optimization Multiobjective cat swarm optimization Pareto dominance
The author Broderick Crawford is supported by grant CONICYT/FONDECYT/REGULAR/1140897 and Ricardo Soto is supported by grant CONICYT/FONDECYT/INICIACION/11130459
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