Proceedings Article10.1145/3460418.3480407
Mobility Data-driven Complete Dispatch Framework for the Ride-hailing Platform
Jiaman Wu,Chenbei Lu,Chenye Wu,Yongli Qin,Qun Li,Nan Ma,Jun Fang +6 more
- 21 Sep 2021
- pp 684-690
TL;DR: In this paper, the authors focus on the complete dispatch for the ride-hailing platform and propose a network flow accelerated algorithm to obtain the dispatch policy when perfect information is available.
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Abstract: Global urbanization has enabled worldwide economic growth over the past decade. Such legend yields a dramatically increasing population for major metropolises, which heavily burdens the transportation sector. The huge personal transportation demands warrant an efficient platform to support dynamic mobile services and their operation. In this work, we focus on the complete dispatch for the ride-hailing platform. We first model the uncertainty in both the supply side and demand side. Then we propose a network flow accelerated algorithm to obtain the dispatch policy when perfect information is available. Then considering the case without perfect information, we further combine network flow formulation and learning framework, and propose the data-driven network flow accelerated algorithm to improve the platform efficiency. In numerical studies, we seek to explore the value of information on the demand side and supply side using real data.
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Citations
Towards Supply-Demand Equilibrium With Ridesharing: An Elastic Order Dispatching Algorithm in MoD System
Shuxin Ge,Xiang Zhao,Tie Qiu,Guobin Wu,Xiaotong Wang +4 more
TL;DR: ERShare is an elastic order dispatching algorithm designed to maximize the order completion rate in MoD systems by achieving long-term supply-demand equilibrium and accurately estimating associating utility based on lane-level features.
ElasticShare: Ridesharing Order Dispatching with Dynamic Supply-demand Distribution
Shuxin Ge,Xiang Zhao,Tie Qiu,Guobin Wu,Xiaotong Wang +4 more
- 19 Jun 2023
TL;DR: ElasticShare, a ridesharing order dispatch method, maximizes order completion rate under dynamic supply-demand distribution by introducing dummy orders and vehicles, solved using a greedy algorithm and correctional order association dispatching algorithm, outperforming state-of-the-art solutions.
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