.png){kind=icon}
.png){kind=icon}
Return
Variable demand and multi-commodity flow in Markovian network equilibrium
.png){kind=icon}
OA
AI
DOI：10.1016/j.automatica.2022.110224.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Markovian network equilibrium generalizes the classical Wardrop equilibrium in network games. At a Markovian network equilibrium, each player of the game solves a Markov decision process instead of a shortest path problem. We propose two novel extensions of Markovian network equilibrium by considering (1) variable demand, which offers the players a quitting option, and (2) multi commodity flow, which allows players to have heterogeneous ending time. We further develop dynamic-programming-based iterative algorithms for the proposed equilibrium problems, together with their arithmetic complexity analysis. Finally, we illustrate our network equilibrium model via a multi-commodity ride-sharing example, and compare the computational efficiency of our algorithms against the state-of-the-art optimization software MOSEK over extensive numerical experiments.(C) 2022 Elsevier Ltd. All rights reserved.
Keywords:
Wardrop equilibrium
Markov decision process
Network optimization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W
Organization
View more organizations