2022/07/13 by Zishuo Zhao, Xi Chen, Zhao, Zishuo +5
Business, Management and Accounting · Engineering · Social Sciences · #Computer Science and Game Theory (cs.GT) #Digital Economy and Work Transformation #FOS: Computer and information sciences #FOS: Mathematics #Optimization and Control (math.OC) #Sharing Economy and Platforms #Transportation and Mobility Innovations
paper · pdf · doi:10.48550/arxiv.2207.06318
openalex publication_date 2022/07/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A major challenge for ridesharing platforms is to guarantee profit and fairness simultaneously, especially in the presence of misaligned incentives of drivers and riders. We focus on the dispatching-pricing problem to maximize the total revenue while keeping both drivers and riders satisfied. We study the computational complexity of the problem, provide a novel two-phased pricing solution with revenue and fairness guarantees, extend it to stochastic settings and develop a dynamic (a.k.a., learning-while-doing) algorithm that actively collects data to learn the demand distribution during the scheduling process. We also conduct extensive experiments to demonstrate the effectiveness of our algorithms.