Hybrid Evolutionary Algorithm for job scheduling under machine maintenance

Authors:
Ruhul Sarker;Mohd Omar;S.M. Kamrul Hasan;Daryl Essam
Affiliations:
School of Engineering and Information Technology, University of New South Wales, ADFA Campus, Canberra 2600, Australia;Institute of Mathematical Sciences, University of Malaya, Lembah Pantai, Kuala Lumpur 50603, Malaysia;School of Engineering and Information Technology, University of New South Wales, ADFA Campus, Canberra 2600, Australia;School of Engineering and Information Technology, University of New South Wales, ADFA Campus, Canberra 2600, Australia
Venue:
Applied Soft Computing
Year:
2013

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Abstract

The job scheduling problem (JSP) belongs to the well-known combinatorial optimization domain. After scheduling, if a machine maintenance issue affects the scheduled processing of jobs, the delivery of jobs must be delayed. In this paper, we have first proposed a Hybrid Evolutionary Algorithm (HyEA) for solving JSPs. We have then analyzed the effect of machine maintenance, whether preventive or breakdown, on the job scheduling. For the breakdown maintenance case, it is required to revise the algorithm to incorporate a rescheduling option after the breakdown occurs. The algorithm has been tested by solving a number of benchmark problems and thence comparing them with the existing algorithms. The experimental results provide a better understanding of job scheduling and the necessary rescheduling operations under process interruption.