Geoprune: Efficiently matching trips in ride-sharing through geometric properties

• Main Authors: XU, Yixin, QI, Jianzhong, BOROVICA-GAJIC, Renata
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Geometric properties; Number of vehicles; Pruning algorithms; Real-world datasets; Selection stages; State of the art; Three orders of magnitude; Time constraints; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/8409; https://ink.library.smu.edu.sg/context/sis_research/article/9412/viewcontent/GeoPrune__Efficiently_Matching_Trips_in_Ride_sharing_Through_Geometric_Properties.pdf
• Institution: Singapore Management University

On-demand ride-sharing is rapidly growing. Matching trip requests to vehicles efficiently is critical for the service quality of ride-sharing. To match trip requests with vehicles, a prune-And-select scheme is commonly used. The pruning stage identifies feasible vehicles that can satisfy the trip co...