Robust scheduling for flexible job shop problems with random machine breakdowns using a quantum behaved particle swarm optimisation

Robust scheduling for flexible job shop problems with random machine breakdowns using a quantum behaved particle swarm optimisation

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Article ID: iaor201525184
Volume: 20
Issue: 1
Start Page Number: 1
End Page Number: 20
Publication Date: Nov 2015
Journal: International Journal of Services and Operations Management
Authors: , ,
Keywords: combinatorial optimization, production: FMS, maintenance, repair & replacement
Abstract:

This paper addresses a robust schedule for a flexible job shop scheduling problem with random machine breakdown. A multi objective framework based on quantum particle swarm optimisation (QPSO) is proposed to generate the predictive schedules that can simultaneously optimise the makespan and the robust measures. The results indicate that the proposed QPSO algorithm is quite effective in reducing makespan in the event that uncertainty is encountered in terms of stochastic machine breakdown. An exhaustive experimental study is conducted to study the effect of different proposed robustness measures on the generated schedules using benchmark problems.

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