102 citations · 179 across the 18 of their papers we have counts for
18 papers
DRL4Route: A Deep Reinforcement Learning Framework for Pick-up and Delivery Route Prediction
Xiaowei Mao, Haomin Wen, Hengrui Zhang +5
Pick-up and Delivery Route Prediction (PDRP), which aims to estimate the future service route of a worker given his current task pool, has received rising attention in recent years…
LaDe: The First Comprehensive Last-mile Delivery Dataset from Industry
Lixia Wu, Haomin Wen, Haoyuan Hu +10
Real-world last-mile delivery datasets are crucial for research in logistics, supply chain management, and spatio-temporal data mining. Despite a plethora of algorithms developed t…
G2PTL: A Pre-trained Model for Delivery Address and its Applications in Logistics System
Lixia Wu, Jianlin Liu, Junhong Lou +5
Text-based delivery addresses, as the data foundation for logistics systems, contain abundant and crucial location information. How to effectively encode the delivery address is a…
An Online Algorithm for Chance Constrained Resource Allocation
Yuwei Chen, Zengde Deng, Yinzhi Zhou +3
This paper studies the online stochastic resource allocation problem (RAP) with chance constraints. The online RAP is a 0-1 integer linear programming problem where the resource co…
AdaptDHM: Adaptive Distribution Hierarchical Model for Multi-Domain CTR Prediction
Jinyun Li, Huiwen Zheng, Yuanlin Liu +3
Large-scale commercial platforms usually involve numerous business domains for diverse business strategies and expect their recommendation systems to provide click-through rate (CT…
Communication-Efficient Decentralized Online Continuous DR-Submodular Maximization
Qixin Zhang, Zengde Deng, Xiangru Jian +3
Maximizing a monotone submodular function is a fundamental task in machine learning, economics, and statistics. In this paper, we present two communication-efficient decentralized…
Online Learning for Non-monotone Submodular Maximization: From Full Information to Bandit Feedback
Qixin Zhang, Zengde Deng, Zaiyi Chen +3
In this paper, we revisit the online non-monotone continuous DR-submodular maximization problem over a down-closed convex set, which finds wide real-world applications in the domai…
Online Primal-Dual Algorithms For Stochastic Resource Allocation Problems
Yuwei Chen, Zengde Deng, Zaiyi Chen +3
This paper studies the online stochastic resource allocation problem (RAP) with chance constraints and conditional expectation constraints. The online RAP is an integer linear prog…
An end-to-end predict-then-optimize clustering method for intelligent assignment problems in express systems
Jinlei Zhang, Ergang Shan, Lixia Wu +3
Express systems play important roles in modern major cities. Couriers serving for the express system pick up packages in certain areas of interest (AOI) during a specific time. How…
Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function
Qixin Zhang, Zengde Deng, Zaiyi Chen +2
In this paper, we revisit Stochastic Continuous Submodular Maximization in both offline and online settings, which can benefit wide applications in machine learning and operations…
Online Allocation Problem with Two-sided Resource Constraints
Qixin Zhang, Wenbing Ye, Zaiyi Chen +3
In this paper, we investigate the online allocation problem of maximizing the overall revenue subject to both lower and upper bound constraints. Compared to the extensively studied…
A Deep Reinforcement Learning Approach for Online Parcel Assignment
Hao Zeng, Qiong Wu, Kunpeng Han +2
In this paper, we investigate the online parcel assignment (OPA) problem, in which each stochastically generated parcel needs to be assigned to a candidate route for delivery to mi…
Balanced Order Batching with Task-Oriented Graph Clustering
Lu Duan, Haoyuan Hu, Zili Wu +4
Balanced order batching problem (BOBP) arises from the process of warehouse picking in Cainiao, the largest logistics platform in China. Batching orders together in the picking pro…
Can Sophisticated Dispatching Strategy Acquired by Reinforcement Learning? - A Case Study in Dynamic Courier Dispatching System
Yujie Chen, Yu Qian, Yichen Yao +5
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 reque…
A Novel Bin Design Problem and High Performance Algorithm for E-commerce Logistics System
Xinhang Zhang, Haoyuan Hu, Longfei Wang +4
Packing cost accounts for a large part of the e-commerce logistics cost. Mining the patterns of customer orders and designing suitable packing bins help to reduce operating cost. I…
GP-CNAS: Convolutional Neural Network Architecture Search with Genetic Programming
Yiheng Zhu, Yichen Yao, Zili Wu +4
Convolutional neural networks (CNNs) are effective at solving difficult problems like visual recognition, speech recognition and natural language processing. However, performance g…
A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem
Lu Duan, Haoyuan Hu, Yu Qian +4
A 3D flexible bin packing problem (3D-FBPP) arises from the process of warehouse packing in e-commerce. An online customer's order usually contains several items and needs to be pa…
Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Method
Haoyuan Hu, Xiaodong Zhang, Xiaowei Yan +2
In this paper, a new type of 3D bin packing problem (BPP) is proposed, in which a number of cuboid-shaped items must be put into a bin one by one orthogonally. The objective is to…