| Report ID: | 08-09-10231-45 |
| Initial Submission Date: | 2008-09-10 |
| Title: | Monotone Approximation of Decision Problems |
| Summary: | Many decision problems exhibit structural properties in the sense that the objective function is a composition of different component functions that can be identified using empirical data. We consider the approximation of such objective functions, subject to general monotonicity constraints on the component functions. Using a constrained B-spline approximation we provide a data-driven robust optimization method for environments that can be sample-sparse. The method is illustrated for the problem of optimal debt settlement in the credit-card industry. |
| Authors: | Chehrazi, Naveed; Weber, Thomas |
| Contact email: | webert@stanford.edu |
| | Number of views : 433 Number of downloads : 1 |
