Green Location-Routing Problem with Delivery Options

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AI and Analytics for Public Health (INFORMS-CSS 2020)

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Abstract

In catering to the needs of the growing e-commerce demand and environmentally friendly urban delivery solutions, parcel logistics companies are increasingly focusing on user experience and sustainable operations such as alternative pickup and delivery options (e.g., lockers) and green delivery vehicles (e.g., electric vehicles). We consider the problem of designing a green location-routing problem with delivery options (GLRP-DO) where the location of lockers to open and the delivery plan of electric vehicles (EVs) are optimized simultaneously to satisfy the total demand, while minimizing the opening cost and handling cost of lockers and the routing cost of EVs. We present an effective branch-and-price (B&P) algorithm to solve it, which is demonstrated to greatly outperform commercial branch-and-cut/bound solvers such as CPLEX in the computational study. Moreover, we provide a thorough analysis of several key parameters of the GLRP-DO (e.g., coverage ranges of lockers and battery driving ranges of EVs), evaluate the impact of delivery options in this green last-mile distribution system and give some useful business insights for parcel logistics companies.

The first author is a student and we would like to compete for the Best Student Paper award.

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Acknowledgements

This work was supported by the National Key R&D Program of China under grant No. 2018AAA0101705, and the National Natural Science Foundation of China under grants 71771130 and 71872092.

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Correspondence to Canrong Zhang .

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Wang, M., Miao, L., Zhang, C. (2022). Green Location-Routing Problem with Delivery Options. In: Yang, H., Qiu, R., Chen, W. (eds) AI and Analytics for Public Health. INFORMS-CSS 2020. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-75166-1_14

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