Article ID: | iaor20105610 |
Volume: | 58 |
Issue: | 4-Part-2 |
Start Page Number: | 1158 |
End Page Number: | 1177 |
Publication Date: | Jul 2010 |
Journal: | Operations Research |
Authors: | Weber Thomas A, Chehrazi Naveed |
Keywords: | credit cards |
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, which simultaneously identifies and solves the decision problem, is illustrated for the problem of optimal debt settlement in the credit-card industry.