Efficient mathematical frameworks for detailed production scheduling in food processing industries

The production scheduling of a real-world multistage food process is considered in this work. An efficient mixed integer programming (MIP) continuous-time model is proposed to address the production problem under study. The overall mathematical framework relies on an efficient modeling approach of t...

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Bibliographic Details
Published in:Computers & chemical engineering 2012-07, Vol.42, p.206-216
Main Authors: Kopanos, Georgios M., Puigjaner, Luis, Georgiadis, Michael C.
Format: Article
Language:English
Subjects:
Aliments
Applied sciences
Biological and medical sciences
Computation
Computer science
control theory
systems
Decisions
Enginyeria química
Exact sciences and technology
Food industries
Food industry
Food industry and trade
Food processing
Food processing industry
Fundamental and applied biological sciences. Psychology
Gelats, sorbets, etc
Ice cream industry
Ice-cream production
Indústria i comerç
Information systems. Data bases
Mathematical models
Memory organisation. Data processing
Mixed integer programming
Operational research and scientific management
Operational research. Management science
Optimization
Organització industrial
Planificació
Producció
Production scheduling
Scheduling, sequencing
Software
Strategy
Àrees temàtiques de la UPC
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Summary:The production scheduling of a real-world multistage food process is considered in this work. An efficient mixed integer programming (MIP) continuous-time model is proposed to address the production problem under study. The overall mathematical framework relies on an efficient modeling approach of the sequencing decisions, the integrated modeling of all production stages, and the inclusion of a set of strong tightening constraints. The simultaneous optimization of all processing stages aims at facilitating the interaction among the different departments of the production facility. Moreover, an alternative MIP-based solution strategy is proposed for dealing with large-scale food processing scheduling problems. Although this method may no guarantee global optimality, it favors low computational requirements and solutions of very good quality. Several problem instances are solved to reveal the salient computational performance and the practical benefits of the proposed MIP formulation and solution strategy.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2011.12.015