Solving the set covering problem with binary cat swarm optimization

BRODERICK CRAWFORD LABRIN, RICARDO JAVIER SOTO DE GIORGIS, Natalia BerrÍos, Franklin Johnson, Fernando Paredes

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

11 Scopus citations

Abstract

The Set Covering Problem is a formal model for many practical optimization problems. It consists in finding a subset of columns in a zero–one matrix such that they cover all the rows of the matrix at a minimum cost. To solve the Set Covering Problem we use a metaheuristic called Binary Cat Swarm Optimization. This metaheuristic is a binary version of Cat Swarm Optimization generated by observing cat behavior. Cats have two modes of behavior: seeking mode and tracing mode. We are the first ones to use this metaheuristic to solve the Set Covering Problem, for this the proposed algorithm has been tested on 65 benchmarks instances.

Original languageEnglish
Title of host publicationAdvances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015 held in conjunction with the 2nd BRICS Congress, CCI 2015, Proceedings
EditorsAlexander Gelbukh, Ying Tan, Swagatam Das, Andries Engelbrecht, Fernando Buarque, Yuhui Shi
PublisherSpringer Verlag
Pages41-48
Number of pages8
ISBN (Print)9783319204659
DOIs
StatePublished - 1 Jan 2015
Event6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015 - Beijing, China
Duration: 25 Jun 201528 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9140
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015
CountryChina
CityBeijing
Period25/06/1528/06/15

Keywords

  • Binary cat swarm optimization
  • Metaheuristic
  • Set covering problem

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