IMPROVED MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION FOR JOB-SHOP SCHEDULING PROBLEMS

  • N.I. Anuar Multimedia University
  • M.H.F. Md Fauadi Universiti Teknikal Malaysia Melaka
  • A. Saptari President University, Indonesia
  • X. Hao Changzhou Institute of Technology

Abstract


The Job-shop Scheduling Problems (JSP) is a typical production scheduling problem widely applied as a single-objective optimization in existing research. However, this is not suitable for cases in the real world, which normally consist of multi-objective criteria. In this paper, a multi-objective Particle Swarm Optimization (MOPSO) for solving JSP is developed, where it involves three key MOPSO attributes to be improved as identified from the literature which are diversity of swarm solutions, exploitation/exploration mechanisms throughout the search process and premature convergence. In order to address the issues related to these attributes, improvement strategies are implemented that include reinitialization of particles, systematic switch of best solutions and Tabu search-based mutation. The computational results in solving benchmark instances demonstrated that the improved MOPSO performs well in terms of finding non-dominated solutions in different regions of the Pareto fronts with a wider spread and producing a higher percentage of solutions in comparison with other established techniques.

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Author Biographies

N.I. Anuar, Multimedia University

Faculty of Engineering and Technology,

Multimedia University, Jalan Ayer Keroh Lama, 75450

Ayer Keroh, Melaka, Malaysia.

M.H.F. Md Fauadi, Universiti Teknikal Malaysia Melaka

Faculty of Manufacturing Engineering,

Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian

Tunggal, Melaka, Malaysia.

A. Saptari, President University, Indonesia

Department of Industrial Engineering,

President University, Cikarang Baru, 17550

Bekasi, Indonesia.

X. Hao, Changzhou Institute of Technology

Changzhou Institute of Technology,

Changzhou, 213032

Jiangsu, China.

Published
2020-12-25
How to Cite
Anuar, N., Md Fauadi, M., Saptari, A., & Hao, X. (2020). IMPROVED MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION FOR JOB-SHOP SCHEDULING PROBLEMS. Journal of Advanced Manufacturing Technology (JAMT), 14(3). Retrieved from https://jamt.utem.edu.my/jamt/article/view/6024
Issue
Vol 14 No 3 (2020): In Press
Section
Articles

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