A bi-objetive Cat Swarm Optimization algorithm for set covering problem

Broderick Crawford, Ricardo Soto, Hugo Caballero, Eduardo Olguín

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publicationArtificial Intelligence Perspectives in Intelligent Systems - Proceedings of 5th Computer Science On-line Conference, CSOC 2016
EditorsRadek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783319336237
StatePublished - 2016
Event5th Computer Science On-line Conference, CSOC 2016 - Prague, Czech Republic
Duration: 27 Apr 201630 Apr 2016

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357


Conference5th Computer Science On-line Conference, CSOC 2016
Country/TerritoryCzech Republic


  • Cat swarm optimization
  • Evolutionary algorithm
  • Multiobjective cat swarm optimization
  • Multiobjective problems
  • Pareto dominance
  • Swarm optimization


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