A Joint Inventory and Transport Capacity Problem With Carbon Emissions

• Published in: IEEE access Vol. 8; pp. 207240 - 207248
• Main Authors: Li, Zhengyi, Hai, Jiangtao
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Carbon; Carbon dioxide; carbon emissions; Carbon tax; Fuels; Integer programming; Inventory; Inventory management; Mixed integer; Optimization; Replenishment; Supply chains; transport capacity; Vehicles
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3038207

This paper considers an inventory system consisting of one supplier and one retailer, and studies a joint inventory policy and transport capacity decision for this inventory system with carbon emissions. The joint decision simultaneously determines the reorder interval of the retailer and the number of the vehicles used to transport the product from the supplier to the retailer while minimizing the inventory replenishment related cost and the carbon emission cost. This paper considers the carbon emissions from holding and replenishing inventory at the retailer, and calculates the carbon emissions based on the reorder interval of the retailer and the number of the vehicles used to transport the product. This problem is formulated as a nonlinear mixed integer programming, and an algorithm is designed to solve the nonlinear mixed integer programming to optimality. The computational results show that the integrated model proposed in this paper can reduce the system-wide cost and the carbon emissions by 5.6% and 14.42% in average, respectively. For the cases that the product with low fixed ordering cost and the vehicle with high fuel consumption, the superiority of the integrated model is more prominent. Besides, the computational results also provide some other management insights.