Abstract
The inherent uncertainties in the ride-hailing market complicate 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. The proposed iterative scheme does not require a potentially 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 assumptions and a careful choice of the step size sequence, obtained by exploiting the specific structure of the SGNEP at hand.
Original language | English |
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Title of host publication | 2022 IEEE 61st Conference on Decision and Control (CDC) |
Pages | 4455-4460 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 2022 |
Event | 2022 IEEE 61st Conference on Decision and Control - Cancun, Mexico Duration: 6 Dec 2022 → 9 Dec 2022 |
Conference
Conference | 2022 IEEE 61st Conference on Decision and Control |
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Abbreviated title | CDC 2022 |
Country/Territory | Mexico |
City | Cancun |
Period | 6/12/22 → 9/12/22 |