Combined planning and scheduling in a divergent production system with co-production: A case study in the lumber industry

Many research initiatives carried out in production management consider process planning and operations scheduling as two separate and sequential functions. However, in certain contexts, the two functions must be better integrated. This is the case in divergent production systems with co-production...

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Bibliographic Details
Published in:Computers & operations research 2011-09, Vol.38 (9), p.1238-1250
Main Authors: Gaudreault, Jonathan, Frayret, Jean-Marc, Rousseau, Alain, D’Amours, Sophie
Format: Article
Language:English
Subjects:
Anytime algorithm
Applied sciences
Constraint programming
Drying
Exact sciences and technology
Integer programming
Integrated planning and scheduling
Inventory control, production control. Distribution
Lumber industry
Mathematical analysis
Mathematical models
Mathematical programming
Mixed integer
Operational research and scientific management
Operational research. Management science
Optimization algorithms
Process planning
Programming
Scheduling
Scheduling, sequencing
Sequential scheduling
Studies
Wood drying and finishing
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Summary:Many research initiatives carried out in production management consider process planning and operations scheduling as two separate and sequential functions. However, in certain contexts, the two functions must be better integrated. This is the case in divergent production systems with co-production (i.e. production of different products at the same time from a single product input) when alternative production processes are available. This paper studies such a context and focuses on the case of drying and finishing operations in a softwood lumber facility. The situation is addressed using a single model that simultaneously performs process planning and scheduling. We evaluate two alternative formulations. The first one is based on mixed integer programming (MIP) and the second on constraint programming (CP). We also propose a search procedure to improve the performance of the CP approach. Both approaches are compared with respect to their capacity to generate good solutions in short computation time.
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2010.10.013