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A Bi-Objetive Cat Swarm Optimization Algorithm for Set Covering Problem

  • Broderick Crawford
  • Ricardo Soto
  • Hugo CaballeroEmail author
  • Eduardo Olguín
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 464)

Abstract

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.

Keywords

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

Notes

Acknowledgments

The author Broderick Crawford is supported by grant CONICYT/FONDECYT/REGULAR/1140897 and Ricardo Soto is supported by grant CONICYT/FONDECYT/INICIACION/11130459

References

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Broderick Crawford
    • 1
    • 2
    • 3
  • Ricardo Soto
    • 1
    • 4
    • 5
  • Hugo Caballero
    • 1
    Email author
  • Eduardo Olguín
    • 2
  1. 1.Pontificia Universidad Católica de ValparaísoValparaísoChile
  2. 2.Universidad San SebastiánSantiago Metropolitan RegionChile
  3. 3.Universidad Central de ChileSantiago Metropolitan RegionChile
  4. 4.Universidad Autónoma de ChileTemucoChile
  5. 5.Universidad Cientifica Del SurLimaPeru

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