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,...
Saved in:
Published in | International journal of production research Vol. 57; no. 21; pp. 6648 - 6664 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
London
Taylor & Francis
02.11.2019
Taylor & Francis LLC |
Subjects | |
Online Access | Get full text |
ISSN | 0020-7543 1366-588X |
DOI | 10.1080/00207543.2019.1571250 |
Cover
Summary: | 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. |
---|---|
Bibliography: | 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 |