A Fuzzy-Logic-Based Methodology for Batch Process Scheduling

We introduce a formal scheduling methodology for batch processes based on fuzzy logic theory. In particular, we present this methodology in the manufacturing context. Our approach takes into account most, if not all, relevant factors in this scheduling problem and models them as fuzzy sets. In the model developed for factory batch process scheduling, the inputs include the "literal" job priority, job's critical ratio, the length of each queue, job's current relative position in its process flow, etc. The model outputs the effective priority value for each queue, based upon which scheduling decisions are made. On numerical examples, we illustrate the use of our model and show the correctness and effectiveness of our model. More importantly, we were able to show that the batch processors' utilization could be increased and jobs' average lateness (with respect to the internal deadline) reduced significantly by applying our methodology.