EURO 2024 Copenhagen
Abstract Submission

EURO-Online login

2184. Optimal carsharing service pricing under decision-dependent demand uncertainty

Invited abstract in session WB-34: Stochastic Optimization: Advanced Applications, stream Stochastic, Robust and Distributionally Robust Optimization.

Wednesday, 10:30-12:00
Room: 43 (building: 303A)

Authors (first author is the speaker)

1. Jiali Deng
Mathematical Sciences, University of Copenhagen
2. Giovanni Pantuso
Mathematical Sciences, University of Copenhagen

Abstract

In carsharing pricing problems, stochastic demand is typically viewed as an exogenous random variable, where the uncertainty is governed by known probability distributions. This assumption neglects the inherent correlation between up-to-date user’s adoption decisions and the released carsharing prices, which makes the stochastic demand decision-dependent. To this end, we come up with an optimal carsharing service pricing problem that incorporates endogenous uncertainty of carsharing demand, specifically by accounting for the decision-dependent distributions of stochastic demand. The problem is formulated as a two-stage mixed-integer stochastic program with decision-dependent uncertainty. We show that the problem can be written as an equivalent mixed-integer bilinear program whose size is exponential in the input parameters. To tackle the computational complexity we adopt a version of the L-shaped method which accounts for decision-dependent distributions. The computational experiments demonstrate empirically that the algorithm converges finitely. In addition, the method outperforms by far a commercial solver used to solve the monolithic formulation, hereby extending the domain of practically tractable problems.

Keywords

Status: accepted

Back to the list of papers