Discrete-time mixed-integer programming models and solution methods for production scheduling in multistage facilities

• Published in: Computers & chemical engineering Vol. 94; pp. 387 - 410
• Main Authors: Merchan, Andres F., Lee, Hojae, Maravelias, Christos T.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 02.11.2016
• Subjects: Approximation; Approximation methods; Chemical engineering; Mathematical models; Production methods; Production scheduling; Programming; Reformulations; Resource scheduling; Resource-constrained project scheduling; Sequential production environments; Tightening constraints; Resource-constrained project scheduling; Sequential production environments; Tightening constraints; Reformulations
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2016.04.034

•We present four new discrete-time MIP scheduling models for multi-stage facilities.•We develop tightening constraints and reformulations combined with priority-based branching.•The proposed models handle important processing features often neglected in the literature.•The proposed methods lead to significant computational enhancements. We address the problem of production scheduling in multi-product multi-stage batch plants. Unlike most of the previous works, which propose continuous-time models, we study discrete-time mixed-integer programming models and solution methods. Specifically, we discuss two models based on network representations of the facility and develop two new models inspired by the Resource-Constrained Project Scheduling Problem. Furthermore, we propose different solution methods, including tightening methods based on processing unit availability, a reformulation based on processing unit occupancy, and an algorithm to refine approximate solutions for large-scale instances. Finally, we present a comprehensive computational study which shows that speedups of up to four orders of magnitude in are observed when our models and methods are compared to existing approaches.