Integrating simulation and genetic algorithm to schedule a dynamic flexible job shop |
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Authors: | M Gholami M Zandieh |
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Affiliation: | (1) Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin, Iran;(2) Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, Tehran, Iran |
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Abstract: | Much of the research on operations scheduling problems has ignored dynamic events in real-world environments where there are
complex constraints and a variety of unexpected disruptions. Besides, while most scheduling problems which have been discussed
in the literature assume that machines are incessantly available, in most real life industries a machine can be unavailable
for many reasons, such as unanticipated breakdowns (stochastic unavailability), or due to a scheduled preventive maintenance
where the periods of unavailability are determined in advance (deterministic unavailability). This paper describes how we
can integrate simulation into genetic algorithm to the dynamic scheduling of a flexible job shop with machines that suffer
stochastic breakdowns. The objectives are the minimization of two criteria, expected makespan and expected mean tardiness.
An overview of the flexible job shops and scheduling under the stochastic unavailability of machines are presented. Subsequently,
the details of integrating simulation into genetic algorithm are described and implemented. Consequently, problems of various
sizes are used to test the performance of the proposed algorithm. The results obtained reveal that the relative performance
of the algorithm for both abovementioned objectives can be affected by changing the levels of the breakdown parameters. |
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Keywords: | Dynamic scheduling Flexible job shop Machine breakdowns Genetic algorithm Simulation |
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