Exploration and Exploitation Measurement in Swarm-Based Metaheuristic Algorithms: An Empirical Analysis

Mohd Najib Mohd Salleh, Kashif Hussain, Shi Cheng, Yuhui Shi, Arshad Muhammad, Ghufran Ullah, Rashid Naseem

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


Swarm-based metaheuristics, inspired from intelligent social behaviors in nature, have achieved wider acceptance among researchers as compared to other population-based methods. The success of any swarm-based algorithm highly depends upon the mechanism of social interaction which maintains the balance between exploration and exploitation. This research examines these two significant cornerstones of top five swarm-based metaheuristics using diversity measurement. The results show that ACO and FA maintained balance between exploration and exploitation throughout iterations thus achieved better results as compared to counterparts taken in this study.
Original languageEnglish
Title of host publicationRecent Advances on Soft Computing and Data Mining
Subtitle of host publicationProceedings of the Third International Conference on Soft Computing and Data Mining (SCDM 2018), Johor, Malaysia, February 06-07, 2018
EditorsRozaida Ghazali, Mustafa Mat Deris, Nazri Mohd Nawi, Jemal H. Abawajy
Number of pages9
ISBN (Electronic)978-3-319-72550-5
ISBN (Print)978-3-319-72549-9
Publication statusPublished - 12 Jan 2018

Publication series

NameAdvances in Intelligent Systems and Computing

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