Solving the Set Covering Problem Using Cat Swarm Optimization Algorithm with a Variable Mixture Rate and Population Restart

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

Abstract

Cat swarm optimization (CSO) is a novel metaheuristic based on swarm intelligence, presented in 2006 has demonstrated great potential generating good results and excellent performances simulating the behavior of domestic cats using two behavior: seeking and tracing mode, this mode are classified using a mixture rate (MR), this parameter finally defines the number of individuals who work by exploring and exploiting. This work presents an improvement structure of a binary cat swarm optimization using a total reboot of the population when loss diversity it is detected.

Original languageEnglish
Title of host publicationApplied Computational Intelligence and Mathematical Methods - Computational Methods in Systems and Software 2017
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Verlag
Pages156-166
Number of pages11
ISBN (Print)9783319676203
DOIs
StatePublished - 2018
Externally publishedYes
EventInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017 - Vsetin, Czech Republic
Duration: 12 Sep 201714 Sep 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume662
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017
Country/TerritoryCzech Republic
CityVsetin
Period12/09/1714/09/17

Keywords

  • Combinatorial Optimization
  • Diversity loss
  • Metaheuristics

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