A New Learnheuristic: Binary SARSA - Sine Cosine Algorithm (BS-SCA)

Marcelo Becerra-Rozas, José Lemus-Romani, Broderick Crawford, Ricardo Soto, Felipe Cisternas-Caneo, Andrés Trujillo Embry, Máximo Arnao A. Molina, Diego Tapia, Mauricio Castillo, José Miguel Rubio

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

Abstract

This paper proposes a novel learnheuristic called Binary SARSA - Sine Cosine Algorithm (BS-SCA) for solving combinatorial problems. The BS-SCA is a binary version of Sine Cosine Algorithm (SCA) using SARSA to select a binarization operator. This operator is required due SCA was created to work in continuous domains. The performance of BS-SCA is benchmarked with a Q-learning version of the learnheuristic. The problem tested was the Set Covering Problem and the results show the superiority of our proposal.

Original languageEnglish
Title of host publicationMetaheuristics and Nature Inspired Computing - 8th International Conference, META 2021, Proceedings
EditorsBernabé Dorronsoro, Farouk Yalaoui, El-Ghazali Talbi, Grégoire Danoy
PublisherSpringer Science and Business Media Deutschland GmbH
Pages127-136
Number of pages10
ISBN (Print)9783030942151
DOIs
StatePublished - 2022
Externally publishedYes
Event8th International Conference on Metaheuristics and Nature Inspired Computing, META 2021 - Virtual, Online
Duration: 27 Oct 202130 Oct 2021

Publication series

NameCommunications in Computer and Information Science
Volume1541 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference8th International Conference on Metaheuristics and Nature Inspired Computing, META 2021
CityVirtual, Online
Period27/10/2130/10/21

Keywords

  • Combinatorial problem
  • Learnheuristic
  • SARSA
  • Sine Cosine Algorithm

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