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Reverse Logistics Modelling of Assets Acquisition in a Liquefied Petroleum Gas Company

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Part of the book series: Mathematics in Industry ((TECMI,volume 30))

Abstract

In the business of liquefied petroleum gas (LPG), the LPG cylinder is the main asset and a correct planning of its needs is critical. This work addresses a challenge, proposed at an European Study Group with Industry by a Portuguese energy sector company, where the objective was to define an assets acquisition plan, i.e., to determine the amount of LPG cylinders to acquire, and when to acquire them, in order to optimize the investment. The used approach to find the solution of this problem can be divided in three phases. First, it is necessary to forecast demand, sales and the return of LPG bottles. Subsequently, this data can be used in a model for inventory management. Classical inventory models, such as the Wilson model, determine the Economic Order Quantity (EOQ) as the batch size that minimizes the total cost of stock management. A drawback of this approach is that it does not take into account reverse logistics, which in this challenge (i.e. the return of cylinders) plays a crucial role. At last, because it is necessary to consider the return rate of LPG bottles, reverse logistic models and closed loop supply chain models are explored.

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Acknowledgements

COST Action TD1409, Mathematics for Industry Network (MI-NET), COST-European Cooperation in Science and Technology; CIDMA-Center for Research and Development in Mathematics and Applications; FCT-Portuguese Foundation for Science and Technology, project UID/MAT/04106/2013. We would like to thank Ana Sapata from University of Evora, and Claudio Henriques, Fabio Henriques e Mariana Pinto from University of Aveiro for their contributions during the European Study Group.

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Correspondence to Cristina Lopes .

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Lopes, C., Correia, A., e Silva, E.C., Monteiro, M., Lopes, R.B. (2019). Reverse Logistics Modelling of Assets Acquisition in a Liquefied Petroleum Gas Company. In: Faragó, I., Izsák, F., Simon, P. (eds) Progress in Industrial Mathematics at ECMI 2018. Mathematics in Industry(), vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-27550-1_18

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