Algorithms for dynamic scheduling in manufacturing, towards digital factories
Flexible Job Shop Scheduling Problems (FJSPs) with generalized time-lags and no-wait constraints
B. Paramon (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Mathijs de Weerdt – Mentor (TU Delft - Algorithmics)
L.R. Planken – Mentor (TU Delft - Research Engineering & Infrastructure Team)
K.C. van den Houten – Mentor (TU Delft - Algorithmics)
J.A. Baaijens – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
This study investigates scheduling strategies for the stochastic duration flexible job-shop problem with no-wait and general time lags constraints (FJSP/NW-GTL). Progress in Constraint Programming (CP) and temporal-networks has renewed interest in assessing the strengths and limitations of different proactive and reactive scheduling approaches. This paper covers the application of a CP-based fully proactive method, a reactive method and STNU-based method on the FJSP/NW-GTL problem comparing results in terms of predetermined objectives and feasibility. In addition, the paper aims to answer how different distributions for task duration affect feasibility and performance. Our results show that strictly proactive methods are infeasible for no-wait constraints and very tight schedules, which lead to adding an online step in the proactive implementation to pursue the comparison between the approaches. With this change, plotting the average makespan across methods by distribution shows that there is not much fluctuation between distribution types in terms of makespan. Moreover, it appears that the proactive method performs the best, followed closely by the reactive method, while the STNU approach results in a notably higher makespan for the same instances. Notably, in terms of feasibility, the proactive and reactive approach have 100% rate of success compared to the STNU approach which is infeasible on 35% of the instances in the dataset.