A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem

Nurul Asyikin, Zainal and Kamal Z., Zamli and Fakhrud, Din (2020) A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem. In: InECCE2019: Proceedings of the 5th International Conference on Electrical, Control & Computer Engineering, 29th July 2019 , Kuantan, Pahang, Malaysia. pp. 219-229., 632. ISBN 978-981-15-2317-5

[img] Pdf
A Modified Symbiotic Organism Search.pdf
Restricted to Repository staff only

Download (559kB) | Request a copy


To date, there are much increasing trends on adopting parameter free meta-heuristic algorithms for solving general optimization problems. With parameter free algorithms, there are no parameter controls for tuning. As such, the adoption of parameter free meta-heuristic algorithms is often straightforward. On the negative note, exploration (i.e. roaming the search space thoroughly) and exploitation (i.e. manipulating the current known best neighbor) are pre-set. As the search spaces are problem dependent, any pre-set exploration and exploitation can lead to entrapment in local optima. In this paper, we investigate the use of Lévy flight to enhance the exploration of a parameter free meta-heuristic algorithm, called Modified Symbiotic Organism Search Algorithm (MSOS), via its population initialization. Our experimentations involving the software module clustering problems have been encouraging, as MSOS gives competitive results against existing selected parameter free meta-heuristic algorithms. For all the given module clustering problems, MSOS generates overall best mean results.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Part of the Lecture Notes in Electrical Engineering book series
Uncontrolled Keywords: Search based software engineering, Software module clustering, Symbiotic organism search
Subjects: Q Science > QA Mathematics
Faculty/Division: Institute of Postgraduate Studies
Faculty of Computing
Depositing User: Noorul Farina Arifin
Date Deposited: 11 Apr 2022 03:04
Last Modified: 11 Apr 2022 03:04
URI: http://umpir.ump.edu.my/id/eprint/33667
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item