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Y. Gao, L. Peng, F. Li, M. Liu, and X. Hu, “Eda-based multi-objective optimization using preference order ranking and multivariate gaussian copula,” in International Symposium on Neural Networks, 2013, pp. 341-350.

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Article

Multi-objective Job Shop Scheduling under Risk Using GA

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


American Journal of Industrial Engineering. 2019, Vol. 6 No. 1, 1-12
DOI: 10.12691/ajie-6-1-1
Copyright © 2019 Science and Education Publishing

Cite this paper:
Jaber S. Alzahrani. Multi-objective Job Shop Scheduling under Risk Using GA. American Journal of Industrial Engineering. 2019; 6(1):1-12. doi: 10.12691/ajie-6-1-1.

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 study, a multi-objective job-shop scheduling model is developed to optimize makespan, maximum job tardiness and maximum and idle time of machines under risk. The model considers multi-jobs and multi-machines. Each task has a specific due date and random processing times of specific probability distribution. The model is solved using @RiskOptimizer.

Keywords