Date of this Version
Annals of Operations Research
We define events so as to reduce the number of events and decision variables needed for modeling batch-scheduling problems such as described in. We propose a new MILP formulation based on this concept, defining non-uniform time periods as needed and decision variables that are not time-indexed. It can handle complicated multi-product/multi-stage machine processes, with production lines merging and diverging, and with minimum and maximum batch sizes. We compare it with earlier models and show that it can solve problems with small to medium demands relative to batch sizes in reasonable computer times.
The final publication is available at Springer via http://dx.doi.org/10.1023/A:1021372029962
continuous-time model, batch, event, scheduling, makespan, integer programming
Wang, S., & Guignard, M. (2002). Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing. Annals of Operations Research, 116 (1), 113-126. http://dx.doi.org/10.1023/A:1021372029962
Date Posted: 27 November 2017
This document has been peer reviewed.