Timezone: »
The Dynamic Pickup and Delivery Problem (DPDP) is an essential problem in the logistics domain, which is NP-hard. The objective is to dynamically schedule vehicles among multiple sites to serve the online generated orders such that the overall transportation cost could be minimized. The critical challenge of DPDP is the orders are not known a priori, i.e., the orders are dynamically generated in real-time. To address this problem, existing methods partition the overall DPDP into fixed-size sub-problems by caching online generated orders and solve each sub-problem, or on this basis to utilize the predicted future orders to optimize each sub-problem further. However, the solution quality and efficiency of these methods are unsatisfactory, especially when the problem scale is very large. In this paper, we propose a novel hierarchical optimization framework to better solve large-scale DPDPs. Specifically, we design an upper-level agent to dynamically partition the DPDP into a series of sub-problems with different scales to optimize vehicles routes towards globally better solutions. Besides, a lower-level agent is designed to efficiently solve each sub-problem by incorporating the strengths of classical operational research-based methods with reinforcement learning-based policies. To verify the effectiveness of the proposed framework, real historical data is collected from the order dispatching system of Huawei Supply Chain Business Unit and used to build a functional simulator. Extensive offline simulation and online testing conducted on the industrial order dispatching system justify the superior performance of our framework over existing baselines.
Author Information
Yi Ma (Tianjin University)
Xiaotian Hao (Tianjin University)
Jianye Hao (Tianjin University)
Jiawen Lu (Tsinghua University, Tsinghua University)
Xing Liu
Tong Xialiang (Huawei Technologies Ltd.)
Mingxuan Yuan (Huawei Noah's Ark Lab)
Zhigang Li (Tianjin University, Tsinghua University)
Jie Tang (Tsinghua University)

Jie Tang is a WeBank Chair Professor of Computer Science at Tsinghua University. He is a Fellow of the ACM, a Fellow of AAAI, and a Fellow of IEEE. His interest is artificial general intelligence (AGI). His research received the SIGKDD Test-of-Time Award (10-year Best Paper). He also received the SIGKDD Service Award. Recently, he puts all efforts into Large Language Models (LLMs): GLM, ChatGLM, etc.
Zhaopeng Meng (School of Computer Software, Tianjin University)
More from the Same Authors
-
2021 : Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning »
Qinkai Zheng · Xu Zou · Yuxiao Dong · Yukuo Cen · Da Yin · Jiarong Xu · YANG YANG · Jie Tang -
2021 : OVD-Explorer: A General Information-theoretic Exploration Approach for Reinforcement Learning »
Jinyi Liu · Zhi Wang · YAN ZHENG · Jianye Hao · Junjie Ye · Chenjia Bai · Pengyi Li -
2021 : HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation »
Boyan Li · Hongyao Tang · YAN ZHENG · Jianye Hao · Pengyi Li · Zhaopeng Meng · LI Wang -
2021 : PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration »
Pengyi Li · Hongyao Tang · Tianpei Yang · Xiaotian Hao · Sang Tong · YAN ZHENG · Jianye Hao · Matthew Taylor · Jinyi Liu -
2022 Poster: Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing »
Yaodong Yang · Guangyong Chen · Weixun Wang · Xiaotian Hao · Jianye Hao · Pheng-Ann Heng -
2022 : ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation »
Pengyi Li · Hongyao Tang · Jianye Hao · YAN ZHENG · Xian Fu · Zhaopeng Meng -
2023 Poster: Reining Generalization in Offline Reinforcement Learning via Representation Distinction »
Yi Ma · Hongyao Tang · Dong Li · Zhaopeng Meng -
2023 Poster: ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation »
Jiazheng Xu · Xiao Liu · Yuchen Wu · Yuxuan Tong · Qinkai Li · Ming Ding · Jie Tang · Yuxiao Dong -
2022 Poster: CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers »
Ming Ding · Wendi Zheng · Wenyi Hong · Jie Tang -
2021 : Invited talk 3 »
Jie Tang -
2021 : HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation Q&A »
Boyan Li · Hongyao Tang · YAN ZHENG · Jianye Hao · Pengyi Li · Zhaopeng Meng · LI Wang -
2021 : HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation »
Boyan Li · Hongyao Tang · YAN ZHENG · Jianye Hao · Pengyi Li · Zhaopeng Meng · LI Wang -
2021 Poster: Adaptive Diffusion in Graph Neural Networks »
Jialin Zhao · Yuxiao Dong · Ming Ding · Evgeny Kharlamov · Jie Tang -
2021 Poster: CogView: Mastering Text-to-Image Generation via Transformers »
Ming Ding · Zhuoyi Yang · Wenyi Hong · Wendi Zheng · Chang Zhou · Da Yin · Junyang Lin · Xu Zou · Zhou Shao · Hongxia Yang · Jie Tang -
2021 Poster: Model-Based Reinforcement Learning via Imagination with Derived Memory »
Yao Mu · Yuzheng Zhuang · Bin Wang · Guangxiang Zhu · Wulong Liu · Jianyu Chen · Ping Luo · Shengbo Li · Chongjie Zhang · Jianye Hao -
2021 Poster: Adaptive Online Packing-guided Search for POMDPs »
Chenyang Wu · Guoyu Yang · Zongzhang Zhang · Yang Yu · Dong Li · Wulong Liu · Jianye Hao -
2021 Poster: UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis »
Zhu Zhang · Jianxin Ma · Chang Zhou · Rui Men · Zhikang Li · Ming Ding · Jie Tang · Jingren Zhou · Hongxia Yang -
2021 Poster: Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning »
Danruo DENG · Guangyong Chen · Jianye Hao · Qiong Wang · Pheng-Ann Heng -
2021 Poster: An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning »
Tianpei Yang · Weixun Wang · Hongyao Tang · Jianye Hao · Zhaopeng Meng · Hangyu Mao · Dong Li · Wulong Liu · Yingfeng Chen · Yujing Hu · Changjie Fan · Chengwei Zhang -
2021 Poster: Dynamic Bottleneck for Robust Self-Supervised Exploration »
Chenjia Bai · Lingxiao Wang · Lei Han · Animesh Garg · Jianye Hao · Peng Liu · Zhaoran Wang -
2020 Poster: Graph Random Neural Networks for Semi-Supervised Learning on Graphs »
Wenzheng Feng · Jie Zhang · Yuxiao Dong · Yu Han · Huanbo Luan · Qian Xu · Qiang Yang · Evgeny Kharlamov · Jie Tang -
2020 Oral: Graph Random Neural Networks for Semi-Supervised Learning on Graphs »
Wenzheng Feng · Jie Zhang · Yuxiao Dong · Yu Han · Huanbo Luan · Qian Xu · Qiang Yang · Evgeny Kharlamov · Jie Tang -
2020 Poster: A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices »
Jiezhong Qiu · Chi Wang · Ben Liao · Richard Peng · Jie Tang -
2020 Poster: CogLTX: Applying BERT to Long Texts »
Ming Ding · Chang Zhou · Hongxia Yang · Jie Tang -
2018 Poster: Bandit Learning with Implicit Feedback »
Yi Qi · Qingyun Wu · Hongning Wang · Jie Tang · Maosong Sun -
2018 Poster: A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents »
YAN ZHENG · Zhaopeng Meng · Jianye Hao · Zongzhang Zhang · Tianpei Yang · Changjie Fan