2022/03/29 by Filippo Fabiani, Fabiani, Filippo, Barbara Franci +1 · 1 citation
Energy · Engineering · Social Sciences · #Computer Science and Game Theory (cs.GT) #Energy, Environment, and Transportation Policies #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Multiagent Systems (cs.MA) #Optimization and Control (math.OC) #Systems and Control (eess.SY) #Transportation Planning and Optimization #Transportation and Mobility Innovations #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2203.15412
openalex publication_date 2022/03/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The presence of uncertainties in the ride-hailing market complicates the pricing strategies of on-demand platforms that compete each other to offer a mobility service while striving to maximize their profit. Looking at this problem as a stochastic generalized Nash equilibrium problem (SGNEP), we design a distributed, stochastic equilibrium seeking algorithm with Tikhonov regularization to find an optimal pricing strategy. Remarkably, the proposed iterative scheme does not require an increasing (possibly infinite) number of samples of the random variable to perform the stochastic approximation, thus making it appealing from a practical perspective. Moreover, we show that the algorithm returns a Nash equilibrium under mere monotonicity assumption and a careful choice of the step size sequence, obtained by exploiting the specific structure of the SGNEP at hand. We finally corroborate our results on a numerical instance of the on-demand ride-hailing market.