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Study on Low-Carbon Emissions in Vehicle Routing Problems with Split Deliveries and Pickups

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LISS 2022 (LISS 2022)

Part of the book series: Lecture Notes in Operations Research ((LNOR))

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Abstract

To reduce the pollution routing problem (PRP) generated by vehicles during logistics distribution, an approximate calculation method for fuel consumption and carbon emissions is introduced from the perspective of energy saving and emission reduction. Based on the vehicle routing problem with split simultaneous deliveries and pickups (VRPSPDP) model, a green VRPSPDP (G-VRPSPDP) model is established. The objective is to find environment-friendly green paths and minimize the total costs. A two-stage heuristic approach is designed to solve the problem. The effectiveness and feasibility of the proposed model and algorithms are verified using numerical experiments. The experimental results show that vehicle speeds, vehicle load rates, travel distances, and the number of routes greatly affect fuel consumption and carbon emissions. Multitype vehicles will decrease the number of vehicles used and route numbers and increase the clustering flexibility. The experimental results also show that it would be necessary for new energy vehicles to enter the transportation market.

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Acknowledgements

This research was supported by the Philosophy and Social Science Research Project of Jiangsu Province Education Commission (Grant No. 2021SJA0903), the National Natural Science Foundation of China (Grant No. 61872077), Jiangsu Provincial Education Commission Humanities and Social Science Research Base Fund (Grant No. 2017ZSJD020), and Jiangsu Provincial Key Construction Laboratory of Internet of Things Application Technology, Taihu University of Wuxithe.

Special thanks to the reviewers and editors for their careful review the manuscript and for their pertinent and useful comments and suggestions.

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Correspondence to Jianing Min .

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Jin, C., Lu, L., Min, J. (2023). Study on Low-Carbon Emissions in Vehicle Routing Problems with Split Deliveries and Pickups. In: Shang, X., Fu, X., Ma, Y., Gong, D., Zhang, J. (eds) LISS 2022. LISS 2022. Lecture Notes in Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-99-2625-1_18

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