Abstract
Ride-sharing systems strive to provide affordable on-demand mobility in urban areas by effectively consolidating incoming transportation requests. To ensure that transportation offers meet travelers’ individual time requirements and constraints, service operators offer multiple pickup times from which travelers can choose. Designing such pickup time offers is challenging due to the uncertainty of both the requirements of the requesting traveler and the efficient fulfillment of future demand. We propose a parametric cost function approximation to balance between maximizing the probability that a traveler will choose an offered pickup time and minimizing the expected vehicle routing effort. We demonstrate the effectiveness of the proposed approach in a comprehensive computational study and provide managerial insights, particularly with respect to the value of information on traveler pickup time requirements.
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