## MULTI-START JAYA ALGORITHM FOR SOFTWARE MODULE CLUSTERING PROBLEM

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Volume 1 (1), July 2018, Pages 87-112

Kamal Z. Zamli^{1}, Abdulrahman Alsewari^{2}, Bestoun S. Ahmed^{3}

^{1 }IBM Centre of Excellence, Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Pahang, Malaysia, This email address is being protected from spambots. You need JavaScript enabled to view it.

^{2 }Faculty of Computer Systems and Software Engineering,Universiti Malaysia Pahang, Pahang, Malaysia, This email address is being protected from spambots. You need JavaScript enabled to view it.

^{3 }Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic, This email address is being protected from spambots. You need JavaScript enabled to view it.

# Abstract

Jaya algorithm has gained considerable attention lately due to its simplicity and requiring no control parameters (i.e. parameter free). Despite its potential, Jaya algorithm is inherently designed for single objective problems. Additionally, Jaya is limited by the intense conflict between exploration (i.e. roams the random search space at the global scale) and exploitation (i.e. neighborhood search by exploiting the current good solution). Thus, Jaya requires better control for exploitation and exploration in order to prevent premature convergence and avoid being trapped in local optima. Addressing these issues, this paper proposes a new multi-objective Jaya variant with a multi-start adaptive capability and Cuckoo search like elitism scheme, called MS-Jaya, to enhance its exploitation and exploration allowing good convergence while permitting more diverse solutions. To assess its performances, we adopt MS-Jaya for the software module clustering problem. Experimental results reveal that MS-Jaya exhibits competitive performances against the original Jaya and state-of-the-art parameter free meta-heuristic counterparts consisting of Teaching Learning based Optimization (TLBO), Global Neighborhood Algorithm (GNA), Symbiotic Optimization Search (SOS), and Sine Cosine Algorithm (SCA).

# Keywords:

Search based Software Engineering, Software Module Clustering Problem, Parameter Free Meta-Heuristic Algorithm, Jaya Algorithm, Computational Intelligence

DOI: https://doi.org/10.32010/26166127.2018.1.1.87.112

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