Artificial bee colony algorithm with directed scout


Saleh R. A. A. , AKAY R.

SOFT COMPUTING, vol.25, no.21, pp.13567-13593, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 25 Issue: 21
  • Publication Date: 2021
  • Doi Number: 10.1007/s00500-021-06062-z
  • Journal Name: SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Page Numbers: pp.13567-13593
  • Keywords: Global optimization, Population-based meta-heuristic, Artificial bee colony, Scout bees, Engineering optimization, GREY WOLF OPTIMIZER, LEVY FLIGHT, SEARCH, PERFORMANCE, STRATEGY, EFFICIENT
  • Erciyes University Affiliated: Yes

Abstract

As a relatively new model, the artificial bee colony algorithm (ABC) has shown impressive success in solving optimization problems. Nevertheless, its efficiency is still not satisfactory for some complex optimization problems. This paper has modified ABC and its other recent variants to improve its performance by modifying the scout phase. This modification enhances its exploitation ability by intensifying the regions in the search space, which probably includes reasonable solutions. The experiments were performed on CEC2014, and CEC2015 benchmark suites, real-life problems. And the proposed modification was applied to basic ABC, Gbest-Guided ABC, Depth First Search ABC, and Teaching-Learning Based ABC, and they were compared with their modified counterparts. The results have shown that our modification can successfully increase the performance of the original versions. Moreover, the proposed modified algorithm was compared with the state-of-the-art optimization algorithms, and it produced competitive results.