A hybrid spherical search and whale optimization algorithm

Jiarui Shi, Jia Yu, Chiyan Lee, Yuki Todo, Shangce Gao*

*Corresponding author for this work

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

2 Scopus citations

Abstract

In recent years, mixed-element heuristics have received increasing attention in optimization algorithms. The spherical search (SS)–a swarm-based meta-heuristic algorithm is used for solving global optimization problems with nonlinear constraints. The whale optimization algorithm (WOA), inspired by the bubble net hunting strategy, mimics the social behavior of humpback whales, whereas the heuristics method usually fall into a so-called “local optima trap”. We proposed a hybrid algorithm based on the whale algorithm and the spherical search optimization hybrid algorithm, so that the two optimization strategies are merged into the presented algorithm which enables both algorithms to work in a co-evolutionary way. Experiment results show that the proposed hybrid algorithm can find the better solutions than some other new algorithms in term of convergence speed and solution accuracy.

Original languageEnglish
Title of host publicationProceedings - 2020 13th International Symposium on Computational Intelligence and Design, ISCID 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages44-49
Number of pages6
ISBN (Electronic)9781728184463
DOIs
StatePublished - 2020/12
Event13th International Symposium on Computational Intelligence and Design, ISCID 2020 - Hangzhou, China
Duration: 2020/12/122020/12/13

Publication series

NameProceedings - 2020 13th International Symposium on Computational Intelligence and Design, ISCID 2020

Conference

Conference13th International Symposium on Computational Intelligence and Design, ISCID 2020
Country/TerritoryChina
CityHangzhou
Period2020/12/122020/12/13

Keywords

  • Computational intelligence
  • Meta-heuristics
  • Optimization
  • Sphere search
  • Whale optimization algorithm

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Information Systems and Management

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