The value of real-time data in stochastic flowshop scheduling: A simulation study for makespan | IEEE Conference Publication | IEEE Xplore

The value of real-time data in stochastic flowshop scheduling: A simulation study for makespan


Abstract:

This paper presents an effort to assess how real-time data can be used to re-sequence jobs in a flowshop where processing times are stochastic and the objective is the mi...Show More

Abstract:

This paper presents an effort to assess how real-time data can be used to re-sequence jobs in a flowshop where processing times are stochastic and the objective is the minimisation of the makespan. By conducting extensive simulation experiments, we try to quantify the advantages of collecting real-time data on the actual completion times of jobs in the shop in order to re-sequence the jobs remaining to be processed. The results show that the benefit of re-sequencing is greatly influenced by the variability of the processing times on the shop floor: There is little advantage when the variability is very high but, for low and intermediate variability levels, re-sequencing provides a way to improve the performance of the initial solution. These results may serve to establish limits on the advantages of using real-time data for improving initial sequencing decisions, at least within the boundaries of our experiments.
Date of Conference: 03-06 December 2017
Date Added to IEEE Xplore: 08 January 2018
ISBN Information:
Electronic ISSN: 1558-4305
Conference Location: Las Vegas, NV, USA

References

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