Abstract— This paper addresses the job shop scheduling problem in the presence of machine breakdowns. In this work, we propose to exploit the advantages of data mining techniques to resolve the problem. We proposed an approach to discover a set of classification rules by using historic scheduling data. Intelligent decisions are then made in real time based on this constructed rules to assign the corresponding dispatching rule in a dynamic job shop scheduling environment. A simulation study is conducted at last with the constructed rules and four other dispatching rules from literature. The experimental results verify the performance of classification rule for minimizing mean tardiness.
Index Terms— Job shop scheduling, classification rules, simulation, machine breakdowns.
N. Said and K. Ghedira are with the Higher Institute of Management of Tunis (University of Tunis), Tunisia (e-mail: said.nesrine@gmail.com, khaled.ghedira@isg.rnu.tn).
W. Mouelhi is with the Higher Institute of Computer Science (University of Tunis ElManar), Tunisia (e-mail: wiem_mouelhi@yahoo.fr).
[PDF]
Cite: N. Said, W. Mouelhi, and K. Ghedira, " Classification Rules for the Job Shop Scheduling Problem with Machine Breakdowns," International Journal of Information and Electronics Engineering vol. 5, no. 4, pp. 300-304, 2015.