Related references
Note: Only part of the references are listed.Surge Pricing and Two-Sided Temporal Responses in Ride Hailing
Bin Hu et al.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT (2022)
DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioning
Xinwu Qian et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2022)
Deep Reinforcement Learning-based Trajectory Pricing on Ride-hailing Platforms
Jianbin Huang et al.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2022)
A mean-field Markov decision process model for spatial-temporal subsidies in ride-sourcing markets
Zheng Zhu et al.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2021)
Spatial-temporal pricing for ride-sourcing platform with reinforcement learning
Chuqiao Chen et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2021)
Ridesharing user equilibrium with nodal matching cost and its implications for congestion tolling and platform pricing
Xu Chen et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2021)
Optimizing matching time intervals for ride-hailing services using reinforcement learning
Guoyang Qin et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2021)
Ride-Sourcing modeling and pricing in non-equilibrium two-sided markets
Mehdi Nourinejad et al.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2020)
Dynamic pricing and matching in ride-hailing platforms
Chiwei Yan et al.
NAVAL RESEARCH LOGISTICS (2020)
Optimal passenger-seeking policies on E-hailing platforms using Markov decision process and imitation learning
Zhenyu Shou et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2020)
Dispatch of autonomous vehicles for taxi services: A deep reinforcement learning approach
Chao Mao et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2020)
An Integrated Decomposition and Approximate Dynamic Programming Approach for On-Demand Ride Pooling
Xian Yu et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2020)
Pricing and equilibrium in on-demand ride-pooling markets
Jintao Ke et al.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2020)
Reward design for driver repositioning using multi-agent reinforcement learning
Zhenyu Shou et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2020)
Dynamic pricing and fleet management for electric autonomous mobility on demand systems
Berkay Turan et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2020)
Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers
Jiaru Bai et al.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT (2019)
Spatial Pricing in Ride-Sharing Networks
Kostas Bimpikis et al.
OPERATIONS RESEARCH (2019)
Model and analysis of labor supply for ride-sharing platforms in the presence of sample self-selection and endogeneity
Hao Sun et al.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2019)
Ridesourcing systems: A framework and review
Hai Wang et al.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2019)
A Deep Value-network Based Approach for Multi-Driver Order Dispatching
Xiaocheng Tang et al.
KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2019)
Surge Pricing Moves Uber's Driver-Partners
Alice Lu et al.
ACM EC'18: PROCEEDINGS OF THE 2018 ACM CONFERENCE ON ECONOMICS AND COMPUTATION (2018)
Large-Scale Order Dispatch in On-Demand Ride-Hailing Platforms: A Learning and Planning Approach
Zhe Xu et al.
KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING (2018)
The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity
Gerard P. Cachon et al.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT (2017)
On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment
Javier Alonso-Mora et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2017)
Surge Pricing Solves the Wild Goose Chase
Juan Camilo Castillo et al.
EC'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON ECONOMICS AND COMPUTATION (2017)
Multi-stage pricing game for collusion-resistant dynamic spectrum allocation
Zhu Ji et al.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2008)
Learning dynamic prices in electronic retail markets with customer segmentation
CVL Raju et al.
ANNALS OF OPERATIONS RESEARCH (2006)
A partially observed Markov decision process for dynamic pricing
Y Aviv et al.
MANAGEMENT SCIENCE (2005)
Share Paper
