Time is on the Side of Grammatical Evolution

Aidan Murphy, Ayman Youssef, Krishn Kumar Gupt, Muhammad Adil Raja, Conor Ryan

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

Abstract

The computational complexity of Evolutionary Algorithms (EAs) is a well-known concern. This paper is concerned with the resource consumption of GELAB, a novel Grammatical Evolution (GE) system implemented in Matlab. GE is an evolutionary technique for program search that manipulates large populations of computer programs over multiple generations. In this paper, we present our reflections on some recently conducted experiments with GELAB. GELAB leverages the power of Matlab to perform hybrid optimization on its individuals. The results show that we can substantially decrease computation time without compromising the accuracy of the system.

Original languageEnglish
Title of host publication2021 International Conference on Computer Communication and Informatics, ICCCI 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728158754
DOIs
Publication statusPublished - 27 Jan 2021
Event2021 International Conference on Computer Communication and Informatics, ICCCI 2021 - Coimbatore, India
Duration: 27 Jan 202129 Jan 2021

Publication series

Name2021 International Conference on Computer Communication and Informatics, ICCCI 2021

Conference

Conference2021 International Conference on Computer Communication and Informatics, ICCCI 2021
Country/TerritoryIndia
CityCoimbatore
Period27/01/2129/01/21

Keywords

  • genetic algorithms
  • Grammatical evolution
  • hybrid optimization
  • simulated annealing
  • swarm optimization

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