A Constraint Programming model for food processing industry: a case for an ice cream processing facility

This paper presents a Constraint Programming (CP) scheduling model for an ice cream processing facility. CP is a mathematical optimisation tool for solving problems either for optimality (for small-size problems) or good quality solutions (for large-size problems). For practical scheduling problems,...

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Vydané v:International journal of production research Ročník 57; číslo 21; s. 6648 - 6664
Hlavní autori: Wari, Ezra, Zhu, Weihang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Taylor & Francis 02.11.2019
Taylor & Francis LLC
Predmet:
Constraint modelling
Constraint Programming
Food processing industry
food processing scheduling
Ice cream
ice cream processing
Integer programming
Linear programming
Mixed integer
Model testing
Optimization
Processing industry
Scale models
Scheduling
ISSN:0020-7543, 1366-588X
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Shrnutí:This paper presents a Constraint Programming (CP) scheduling model for an ice cream processing facility. CP is a mathematical optimisation tool for solving problems either for optimality (for small-size problems) or good quality solutions (for large-size problems). For practical scheduling problems, a single CP solution model can be used to optimise daily production or production horizon extending for months. The proposed model minimises a makespan objective and consists of various processing interval and sequence variables and a number of production constraints for a case from a food processing industry. Its performance was compared to a Mixed Integer Linear Programming (MILP) model from the literature for optimality, speed, and competence using the partial capacity of the production facility of the case study. Furthermore, the model was tested using different product demand sizes for the full capacity of the facility. The results demonstrate both the effectiveness, flexibility, and speed of the CP models, especially for large-scale models. As an alternative to MILP, CP models can provide a reasonable balance between optimality and computation speed for large problems.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2019.1571250