Efficient mathematical frameworks for detailed production scheduling in food processing industries

• 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
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2011.12.015

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.