Journal of Industrial Management Perspective

Journal of Industrial Management Perspective

Modeling and Solving Bi-Objective Flexible Job Shop Scheduling with Parallel Machines and Dual Human-Machine Resources

Document Type : Original Article

Authors
Maryam Hajibabaie 1
Javad Behnamian 2
1 Msc, Bu-Ali Sina University.
2 Associate Professor, Bu-Ali Sina University.
10.52547/jimp.12.3.203
Abstract
This paper studies the flexible job shop scheduling problem with parallel machines by considering cleaner production criteria, dual human-machine resources, job release date, and machine speed-dependent processing time. The objective functions of this problem include minimizing the sum of earliness and tardiness and the speed increasing. Here it is assumed that the speed of the machines can be increased to reduce the completion time while the increasing the speed leads to increasing the noise pollution in the production environment, and due to the cleaner production approach which is a preventive approach, an attempt has been made to reduce the amount of noise pollution by minimizing the speed increasing. In this regard, first, a mixed integer-programming model was developed, and since the model is bi-objective and NP-hard, a NRGA is proposed and the obtained results are compared with the NSGAII considering some multi-objectives criteria. The results show that the proposed algorithm considering the MID criterion in instances with 10 and 25 jobs and considering the RAS criterion in instances with 25 and 100 jobs have better performance compare to the NSGAII. Furthermore, the TOPSIS method is also used for analysis and the results show the efficiency of the proposed algorithm.
Keywords
Flexible Job Shop Scheduling
Noise Pollution
Dual Human-Machine Resources
Non-Dominated Ranked Genetic Algorithm
TOPSIS
Subjects
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