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A real time data mining rules selection model for the Job Shop Scheduling Problem

Abstract : Finding the best Dispatching Rule for a Job Shop Scheduling Problem is a tedious task, both time and cost consuming. Since there is no rule that can outperform the others, in this paper we propose an approach able to affect in real-time a different Dispatching Rule for each machine while minimizing makespan. This approach is based on simulation and Data Mining. Experimentations show that the proposed system returns good results in both makespan and processing time needs.
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https://hal-uphf.archives-ouvertes.fr/hal-03659568
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Submitted on : Thursday, May 5, 2022 - 10:26:22 AM
Last modification on : Friday, May 6, 2022 - 3:38:42 AM

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  • HAL Id : hal-03659568, version 1

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Mohamed Habib Zahmani, Baghdad Atmani, Abdelghani Bekrar, Nassima Aissani. A real time data mining rules selection model for the Job Shop Scheduling Problem. CIE 45: 2015 International Conference on Computers and Industrial Engineering, Oct 2015, Metz, France. ⟨hal-03659568⟩

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