This thesis focuses on optimization on a generic objective function based on reflected Brownian motion (RBM). We investigate in several approaches including the partial differential equation approach where we write our objective function in terms of a Hamilton-Jacobi-Bellman equation using the dynamic programming principle and the gradient descent approach where we use two different gradient estimators. We provide extensive numerical results with the gradient descent approach and we discuss the difficulties and future study opportunities for this problem.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/9963623 |
| Date | 17 October 2019 |
| Creators | Zihe Zhou (7483880) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Optimizing_Reflected_Brownian_Motion_A_Numerical_Study/9963623 |
Page generated in 0.0018 seconds