Increased Efficiency of the Artificial Bee Colony Algorithm Using the Pheromone Technique

Authors

  • A. H. Alaidi Programming Department, Computer Science and Information Technology College, Wasit University, Iraq
  • C. Soong Der College of Computing and Informatics, Universiti Tenaga Nasional, Malaysia
  • Y. Weng Leong College of Computing and Informatics, Universiti Tenaga Nasional, Malaysia
Volume: 12 | Issue: 6 | Pages: 9732-9736 | December 2022 | https://doi.org/10.48084/etasr.5305

Received: 1 September 2022 | Revised: 15 September 2022 | Accepted: 17 September 2022 | Online: 15 December 2022


Corresponding author: A. H. Alaidi

Abstract

Artificial Bee Colony (ABC) is a powerful metaheuristic algorithm inspired by the behavior of a honey bee swarm. ABC suffers from poor exploitation and, in some cases, poor exploration. Ant Colony Optimization (ACO) is another metaheuristic algorithm that uses pheromones as a guide for an ant to find its way. This study used a pheromone technique from ACO on ABC to enhance its exploration and exploitation. The performance of the proposed method was verified through twenty instances from TSPLIB. The results were compared with the original ABC method and showed that the proposed method leverages the performance of ABC.

Keywords:

artificial bee colony, pheromone, ant colony optimization

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How to Cite

[1]
Alaidi, A.H., Soong Der, C. and Weng Leong, Y. 2022. Increased Efficiency of the Artificial Bee Colony Algorithm Using the Pheromone Technique. Engineering, Technology & Applied Science Research. 12, 6 (Dec. 2022), 9732–9736. DOI:https://doi.org/10.48084/etasr.5305.

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