This paper studies a supply chain consisting of multiple suppliers and a single buyer. It considers the case where a set of heterogeneous trucks is used for transporting products, and develops a mathematical model that coordinates the supply chain. The purpose of this paper is to minimise the costs of producing and delivering a product as well as carbon emissions resulting from transportation. In addition, the authors analyse how imposing a tax on carbon emissions impacts the delivery of products from the suppliers to the buyer.
It is assumed that heterogeneous vehicles are used for transporting products, which have different performance and cost attributes. A mathematical model that considers both operating costs and carbon emissions from transportation is developed. The impact of vehicle attributes on lot sizing and routing decisions is studied with the help of numerical examples and a sensitivity analysis.
The analysis shows that considering carbon emissions in coordinating a supply chain leads to changes in the routing of vehicles. It is further shown that if carbon emissions lead to costs, routes are changed in such a way that vehicles travel long distances empty or with a low vehicle load to reduce fuel consumption and therewith emissions.
Several areas for future work are highlighted. The study of alternative supply chain structures, for example structures which include logistics service providers, or the investigation of different functional relationships between vehicle load and emission generation offer possibilities for extending the model.
The paper is one of the first to study the use of heterogeneous vehicles in an inventory model of a supply chain, and one of the few supply chain inventory models that consider ecological aspects.
The authors are grateful to the anonymous referees for their constructive comments that helped to improve an earlier version of this paper.
Glock, C.H. and Kim, T. (2015), "Coordinating a supply chain with a heterogeneous vehicle fleet under greenhouse gas emissions", The International Journal of Logistics Management, Vol. 26 No. 3, pp. 494-516. https://doi.org/10.1108/IJLM-09-2013-0107
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