Loading…
Integrated production and distribution scheduling with lifespan constraints
We consider an integrated production and distribution scheduling problem in a make-to-order business scenario. A product with a short lifespan (e.g., perishable or seasonal) is produced at a single production facility with a limited production rate. This means that the product expires in a constant...
Saved in:
Published in: | Annals of operations research 2014-02, Vol.213 (1), p.293-318 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | We consider an integrated production and distribution scheduling problem in a make-to-order business scenario. A product with a short lifespan (e.g., perishable or seasonal) is produced at a single production facility with a limited production rate. This means that the product expires in a constant time after its production is finished. Orders are received from a set of geographically dispersed customers, where a demand for the product and a time window for the delivery is associated with each customer for the planning period. A single vehicle with non-negligible traveling times between the locations is responsible for the deliveries. Due to the limited production and distribution resources, possibly not all customers may be supplied within their time windows or the lifespan. The problem consists in finding a selection of customers to be supplied such that the total satisfied demand is maximized. We extend the work by Armstrong et al. (Annals of Operations Research 159(1):395–414,
2008
) on the problem for fixed delivery sequences by pointing out an error in their branch and bound algorithm and presenting a corrected variant. Furthermore, we introduce model extensions for handling delays of the production start as well as for variable production and distribution sequences. Efficient heuristic solution algorithms and computational results for randomly generated instances are presented. |
---|---|
ISSN: | 0254-5330 1572-9338 |
DOI: | 10.1007/s10479-012-1197-z |