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Growing Science » International Journal of Industrial Engineering Computations » Upstream logistic transport planning in the oil-industry: a case study

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 11 Issue 2 pp. 221-234 , 2020

Upstream logistic transport planning in the oil-industry: a case study Pages 221-234 Right click to download the paper Download PDF

Authors: Diego G. Rossit, Mauro Ehulech Gonzalez, Fernando Tohmé, Mariano Frutos

DOI: 10.5267/j.ijiec.2019.9.002

Keywords: Decision support tools, Oil industry, Upstream logistics, Inland transportation

Abstract: Nowadays, oil companies have to deal with an increasingly competitive environment. In this sense, the optimization of operational processes to enhance efficiency is crucial. This article addresses the design of a decision support tool for the inland upstream transport logistics in the oil industry based on a case of study in Argentina. This problem is traditionally difficult to solve for managers due to the large number of demand facilities scattered on a large geographic area that have to be served and the consideration of several operational requirements, such as maximum allowable travel times for vehicles, availability of a limited fleet size with a small number of drivers, plus the usual demand constraints as well as those arising from security risks derived from the incompatibility of chemical products. A novel mathematical formulation and a constructive heuristic are proposed in order to address this problem. The results allow to reduce the time that the company spends for obtaining a feasible distribution plan that minimizes the time horizon of the distribution schedule provided to the clients and enhances customer satisfaction.

How to cite this paper
Rossit, D., Gonzalez, M., Tohmé, F & Frutos, M. (2020). Upstream logistic transport planning in the oil-industry: a case study.International Journal of Industrial Engineering Computations , 11(2), 221-234.

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Journal: International Journal of Industrial Engineering Computations | Year: 2020 | Volume: 11 | Issue: 2 | Views: 2850 | Reviews: 0

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