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

•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 s...

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Vydané v:Computers & chemical engineering Ročník 94; s. 387 - 410
Hlavní autori: Merchan, Andres F., Lee, Hojae, Maravelias, Christos T.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 02.11.2016
Predmet:
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
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Shrnutí:•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.
Bibliografia:ObjectType-Article-1
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ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2016.04.034