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Editor-in-chief

 
Faculty of Science, University of Brunei Darussalam, Brunei Darussalam   
" It is a great honor to serve as the editor-in-chief of IJIEE. I'll work together with the editorial team. Hopefully, IJIEE will be recognized among the readers in the related field."
IJIEE 2015 Vol.5(4): 300-304 ISSN: 2010-3719
DOI: 10.7763/IJIEE.2015.V5.548

Classification Rules for the Job Shop Scheduling Problem with Machine Breakdowns

N. Said, W. Mouelhi, and K. Ghedira
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.

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