Efficient priority rules for dynamic sequencing with sequence-dependent setups

Xanthopoulos, A.; Koulouriotis, D.; Gasteratos, A.; Ioannidis, S.

Abstract: This article addresses the problem of dynamic sequencing on n identical parallel machines with stochastic arrivals, processing times, due dates and sequence-dependent setups. The system operates under a completely reactive scheduling policy and the sequence of jobs is determined with the use of dispatching rules. Seventeen existing dispatching rules are considered including standard and setup-oriented rules. The performance of the system is evaluated by four metrics. An experimental study of the system is conducted where the effect of categorical and continuous system parameters on the objective functions is examined. In light of the results from the simulation experiments, a parameterized priority rule is introduced and tested. The simulation output is analyzed using rigorous statistical methods and the proposed rule is found to produce significantly better results regarding the metrics of mean cycle time and mean tardiness in single machine cases. In respect to three machine cases, the proposed rule matches the performance of the best rule from the set of existing rules which were studied in this research for three metrics.

How to cite this paper

        APA: Xanthopoulos, A., Koulouriotis, D., Gasteratos, A & Ioannidis, S. (2016). Efficient priority rules for dynamic sequencing with sequence-dependent setups. International Journal of Industrial Engineering Computations, 7(3), 367-384.
    

        Chicago/Turabian: Xanthopoulos, A., Koulouriotis, D., Gasteratos, A & Ioannidis, S. 2016. "Efficient priority rules for dynamic sequencing with sequence-dependent setups." International Journal of Industrial Engineering Computations 7, no. 3 (2016): 367-384.
    

        AMA: Xanthopoulos, A., Koulouriotis, D., Gasteratos, A & Ioannidis, S. Efficient priority rules for dynamic sequencing with sequence-dependent setups. International Journal of Industrial Engineering Computations. 2016;7(3):367-384.
    

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