A predict-then-optimize couriers allocation framework for emergency last-mile logistics

K Xia, L Lin, S Wang, H Wang, D Zhang… - Proceedings of the 29th …, 2023 - dl.acm.org
In recent years, emergency last-mile logistics (ELML) have played an essential role in urban
emergencies. The efficient allocation of couriers in ELML is of practical significance to …

Towards equitable assignment: Data-driven delivery zone partition at last-mile logistics

B Guo, S Wang, H Wang, Y Liu, F Kong… - Proceedings of the 29th …, 2023 - dl.acm.org
The popularity of online e-commerce has promoted the rapid development of last-mile
logistics in recent years. In last-mile services, to ensure delivery efficiency and enhance user …

GCRL: Efficient Delivery Area Assignment for Last-mile Logistics with Group-based Cooperative Reinforcement Learning

H Wang, S Wang, Y Yang… - 2023 IEEE 39th …, 2023 - ieeexplore.ieee.org
Last-mile logistics is the final step of the delivery process from a transit station to customers.
In last-mile logistics systems, a city is divided into many delivery areas for couriers to finish …

[PDF][PDF] A prediction-and-scheduling framework for efficient order transfer in logistics

W Lyu, H Wang, Y Song, Y Liu, T He… - Proceedings of the Thirty …, 2023 - ijcai.org
Order Transfer from the transfer center to delivery stations is an essential and expensive part
of the logistics service chain. In practice, one vehicle sends transferred orders to multiple …

VeLP: Vehicle Loading Plan Learning from Human Behavior in Nationwide Logistics System

S Duan, F Lyu, X Zhu, Y Ding, H Wang… - Proceedings of the …, 2023 - dl.acm.org
For a nationwide logistics transportation system, it is critical to make the vehicle loading
plans (ie, given many packages, deciding vehicle types and numbers) at each sorting and …

[PDF][PDF] Data-driven order assignment for last mile delivery

S Liu, L He, ZJM Shen - SSRN Electronic Journal, 2018 - www-2.rotman.utoronto.ca
We study how delivery data can be applied to improve on-time performance in last mile
delivery service. Motivated by a food delivery service provider, we discuss a data-driven …

Can sophisticated dispatching strategy acquired by reinforcement learning?-a case study in dynamic courier dispatching system

Y Chen, Y Qian, Y Yao, Z Wu, R Li, Y Zhou… - arXiv preprint arXiv …, 2019 - arxiv.org
In this paper, we study a courier dispatching problem (CDP) raised from an online pickup-
service platform of Alibaba. The CDP aims to assign a set of couriers to serve pickup …

A prescriptive analytics framework for efficient E-commerce order delivery

S Kandula, S Krishnamoorthy, D Roy - Decision Support Systems, 2021 - Elsevier
Achieving timely last-mile order delivery is often the most challenging part of an e-commerce
order fulfillment. Effective management of last-mile operations can result in significant cost …

[HTML][HTML] Data-driven optimization for last-mile delivery

H Chu, W Zhang, P Bai, Y Chen - Complex & Intelligent Systems, 2023 - Springer
This paper considers how an online food delivery platform can improve last-mile delivery
services' performance using multi-source data. The delivery time is one critical but uncertain …

A general framework for unmet demand prediction in on-demand transport services

W Li, J Cao, J Guan, S Zhou, G Liang… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Emerging on-demand transport services, such as Uber and GoGoVan, usually face the
dilemma of demand supply imbalance, meaning that the spatial distributions of orders and …