Trajectory-Based Convergence Acceleration of Evolutionary Algorithms

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

Abstract

Evolutionary algorithms are heuristic, nature-inspired search methods based on the concept of evolution and survival of the fittest. While they have proven to be effective across a variety of problems they are often inefficient as they do not use information generated during the search and could therefore require extensive computer resources to converge. To address this issue this paper proposes a new method for evolutionary convergence acceleration which is inspired by the method of successive-over-relation for the solution of linear equations sets. The main concept is to determine the direction in which the population centroid has shifted between successive generations, which suggests a favourable direction towards an optimum. The population of solutions is then propagated along that direction to accelerate its convergence. The proposed algorithm is flexible and can be applied to a variety of evolutionary algorithms. An extensive performance analysis based on representative test functions shows the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publication27th International Computer Science and Engineering Conference 2023, ICSEC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages461-465
Number of pages5
ISBN (Electronic)9798350342109
DOIs
StatePublished - 2023
Event27th International Computer Science and Engineering Conference, ICSEC 2023 - Koh Samui , Surat Thani, Thailand
Duration: 13 Sep 202315 Sep 2023

Publication series

Name27th International Computer Science and Engineering Conference 2023, ICSEC 2023

Conference

Conference27th International Computer Science and Engineering Conference, ICSEC 2023
Country/TerritoryThailand
CityKoh Samui , Surat Thani
Period13/09/2315/09/23

Keywords

  • Convergence
  • Evolutionary computing
  • Iterative solution techniques
  • Optimization

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Software
  • Information Systems and Management
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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