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G. Zhang, X. Shao, P. Li, and L. Gao, "An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem," Computers & Industrial Engineering, vol. 56, pp. 1309-1318, 2009.

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Article

Multi-objective Job Shop Scheduling Using Pre-emptive Constraint Procedure

1Department of Industrial Engineering, Engineering College at Alqunfudah, Umm Al-Qura University, Saudi Arabia


American Journal of Modeling and Optimization. 2019, Vol. 7 No. 1, 8-13
DOI: 10.12691/ajmo-7-1-2
Copyright © 2019 Science and Education Publishing

Cite this paper:
Jaber S. Alzahrani. Multi-objective Job Shop Scheduling Using Pre-emptive Constraint Procedure. American Journal of Modeling and Optimization. 2019; 7(1):8-13. doi: 10.12691/ajmo-7-1-2.

Correspondence to: Jaber  S. Alzahrani, Department of Industrial Engineering, Engineering College at Alqunfudah, Umm Al-Qura University, Saudi Arabia. Email: jszahrani@ uqu.edu.sa

Abstract

In this paper, a multi-objective job shop scheduling through the pre-emptive constraint procedure has been formulated to optimize makespan, total earliness and total tardiness. The effectiveness of the model is studied through eighteen 3J*3M and three 10J*10M problems. The model is solved using Mosel language with Xpress software.

Keywords