Production Scheduling in Multiproduct Multistage Semicontinuous Food Processes

This works presents a novel mixed-integer programming framework and a solution strategy for the optimal production scheduling of multiproduct and multistage food process industries, such as ice-cream production facilities, studied in detail. The overall mathematical framework relies on an efficient...

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Bibliographic Details
Published in:Industrial & engineering chemistry research 2011-05, Vol.50 (10), p.6316-6324
Main Authors: Kopanos, Georgios M, Puigjaner, Luis, Georgiadis, Michael C
Format: Article
Language:English
Subjects:
Aliments
Anàlisi de processos de negoci i de fabricació
Applied sciences
Biological and medical sciences
Chemical engineering
Direcció d'operacions
Economia i organització d'empreses
Economics. Management. Design assessment
Enginyeria agroalimentària
Exact sciences and technology
Food engineering
Food industries
Food industry and trade
Fundamental and applied biological sciences. Psychology
General aspects
Indústria de la llet
Indústria i comerç
Indústries agroalimentàries
Mathematical models
Models matemàtics
Process Design and Control
Àrees temàtiques de la UPC
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Summary:This works presents a novel mixed-integer programming framework and a solution strategy for the optimal production scheduling of multiproduct and multistage food process industries, such as ice-cream production facilities, studied in detail. 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 strong valid integer cuts in the formulation. The simultaneous optimization of all processing stages increases the plant production capacity, reduces the production cost for final products, and facilitates interaction among the different departments of the production facility. Several instances of a real-life industrial case study concerning ice-cream production have been solved to optimality to illustrate the applicability and efficiency of the overall modeling and solution approach.
ISSN:0888-5885
1520-5045
DOI:10.1021/ie2001617