Scheduling of Multiproduct Multistage Batch Plants with Uncertain Processing Times: an Innovative Constraint Programming Approach

Due to the intrinsic uncertainty and dynamics of industrial environments schedulers must continually reconcile what is expected with what actually happens. One of the most common sources of uncertainty encountered at the operational level is the one associated with variable processing times. This work contributes in the area of proactive scheduling by developing an innovative Constraint Programming (CP) model able to cope with uncertain processing times at the decision stage, prior to scheduling and without resorting to the generation of scenarios. The application of the model to various instances of three case studies shows that the approach is computationally efficient. In addition, when the obtained schedules are compared with the agendas that were reached by a deterministic CP formulation, it is shown that they absorb the variability of the processing times better.