Optimizing the wine transportation process from bottling plants to ports

Franco Basso (), Juan Pablo Contreras (), Raúl Pezoa (), Alejandro Troncozo () and Mauricio Varas ()
Additional contact information
Franco Basso: Pontificia Universidad Católica de Valparaíso
Juan Pablo Contreras: Universidad Católica del Norte
Raúl Pezoa: Universidad Diego Portales
Alejandro Troncozo: Universidad Diego Portales
Mauricio Varas: Universidad del Desarrollo

Operational Research, 2023, vol. 23, issue 2, No 15, 28 pages

Abstract: Abstract The wine industry is a highly competitive sector for which any efficiency improvement in the wine supply chain plays a critical role in maintaining or increasing profitability. Literature shows several successful applications of operational research tools at each stage of the wine production process. However, unlike other stages, the transportation and distribution phase has not been given the same attention in the specialized literature. To bridge this gap, this article proposes an integer linear programming model to jointly determine a plan for the bottling and transportation of products to ports in order to minimize inventory, freight, and delay costs. This model can be optimally solved in less than one day for small instances of up to 25 jobs. In practice, however, some industrial instances can easily exceed 200 jobs, which precludes the use of this model to support decision-making. To cope with this issue, we devise a two-stage procedure that generates good-quality solutions for industrial-size instances of this problem in reasonable computing times. Particularly, we show that the GAP of the proposed heuristic solution is relatively low for a wide range of instances. Finally, a case study is conducted on a medium-sized Chilean winery we worked with, where the planning generated by the proposed heuristic reduces the costs corresponding to the transportation stage by 45.3% in the best case, compared to the initial planning of the winery.

Keywords: Wine supply chain; Transportation; Integer programming; Heuristic; Case study (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s12351-023-00778-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:operea:v:23:y:2023:i:2:d:10.1007_s12351-023-00778-6

Ordering information: This journal article can be ordered from
https://www.springer ... search/journal/12351

DOI: 10.1007/s12351-023-00778-6

Access Statistics for this article

Operational Research is currently edited by Nikolaos F. Matsatsinis, John Psarras and Constantin Zopounidis

More articles in Operational Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().