This repository is used to collect the MATLAB files created to solve a non-convex optimization problem related to the article of Zhu and Savla (2018) [On the stability of optimal bayesian persuasion strategy under a mistrust dynamics in routing games. In 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pages 92–99. IEEE.].
Full Thesis Here
The current focus of navigation apps is to recommend drivers the fastest road to reach a specific destination. While pleasing the individual driver, this behavior contributes to higher levels of traffic congestion. In other words, navigation apps focus on the selfish needs of users and do not align with social welfare. Research has shown that concepts of Bayesian persuasion and Wardrop equilibrium allow the possibility for information design, whereby the navigation app can strategically pick what information to reveal to its users in order to achieve the desired social objective of mitigating traffic congestion.
This study aims at extending upon an existing mathematical model developed with the intention of alleviating traffic congestion. In particular, the research focuses on translating an optimization problem into a functional algorithm. In order to achieve said objective, the programming language MATLAB is used in combination with a brute force method that attempts to solve a non-convex optimization problem. Results give interesting insights into how numerically efficient methods could be constructed to find the optimum solution. In particular, a clear repetitive structure of both the optimal objective function value and the feasibility constraints at the optimum was found.