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Managing risk in production scheduling under uncertain disruption

Published online by Cambridge University Press:  09 June 2015

Ruhul Sarker ,
Daryl Essam ,
S.M. Kamrul Hasan  and
A.N. Mustafizul Karim
Ruhul Sarker*
Affiliation:
School of Engineering and Information Technology, University of New South Wales at Canberra, ADFA Campus, Canberra, Australia
Daryl Essam
Affiliation:
School of Engineering and Information Technology, University of New South Wales at Canberra, ADFA Campus, Canberra, Australia
S.M. Kamrul Hasan
Affiliation:
School of Engineering and Information Technology, University of New South Wales at Canberra, ADFA Campus, Canberra, Australia
A.N. Mustafizul Karim
Affiliation:
Department of Manufacturing and Materials Engineering, International Islamic University Malaysia, Gombak, Kuala Lumpur, Malaysia
*
Reprint requests to: Ruhul Sarker, School of Engineering and Information Technology, University of New South Wales at Canberra, ADFA Campus, Canberra, Australia2600. E-mail: r.sarker@adfa.edu.au
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Abstract

The job scheduling problem (JSP) is considered as one of the most complex combinatorial optimization problems. JSP is not an independent task, but is rather a part of a company business case. In this paper, we have studied JSPs under sudden machine breakdown scenarios that introduce a risk of not completing the jobs on time. We have first solved JSPs using an improved memetic algorithm and extended the algorithm to deal with the disruption situations, and then developed a simulation model to analyze the risk of using a job order and delivery scenario. This paper deals with job scheduling under ideal conditions and rescheduling under machine breakdown, and provides a risk analysis for a production business case. The extended algorithm provides better understanding and results than existing algorithms, the rescheduling shows a good way of recovering from disruptions, and the risk analysis shows an effective way of maximizing return under such situations.

Keywords

DisruptionGenetic AlgorithmJob SchedulingMemetic AlgorithmRisk Analysis
Type
Regular Articles
Information
AI EDAM , Volume 30 , Special Issue 3: System Architecture Design , August 2016 , pp. 289 - 299
Copyright
Copyright © Cambridge University Press 2015 

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