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

Mohamed Habib Zahmani , Baghdad Atmani , Abdelghani Bekrar (1) , Nassima Aissani

1 LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201

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.

Mots clés: Artificial intelligence; Data mining; Dispatching rules; Job shop; Simulation

Domaines: Sciences de l'ingénieur [physics]; Automatique / Robotique

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⟩