An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products
M.A.F. Belo-Filho,
P. Amorim and
B. Almada-Lobo
International Journal of Production Research, 2015, vol. 53, issue 20, 6040-6058
Abstract:
Production and distribution problems with perishable goods are common in many industries. For the sake of the competitiveness of the companies, the supply chain planning of products with restricted lifespan should be addressed with an integrated approach. Particularly, at the operational level, the sizing and scheduling of production lots have to be decided together with vehicle routing decisions to satisfy the customers. However, such joint decisions make the problems hard to solve for industries with a large product portfolio. This paper proposes an adaptive large neighbourhood search (ALNS) framework to tackle the problem. This metaheuristic is well known to be effective for vehicle routing problems. The proposed approach relies on mixed-integer linear programming models and tools. The ALNS outperforms traditional procedures of the literature, namely, exact methods and fix-and-optimize, in terms of quality of the solution and computational time of the algorithms. Nine in ten runs of ALNS yielded better solutions than traditional procedures, outperforming on average 12.7% over the best solutions provided by the latter methods.
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2015.1010744 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:53:y:2015:i:20:p:6040-6058
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2015.1010744
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().