Monotone Approximation of Decision Problems

Operations Research, Forthcoming

35 Pages Posted: 9 Jan 2009 Last revised: 29 Apr 2010

See all articles by Naveed Chehrazi

Naveed Chehrazi

Washington University in St. Louis - John M. Olin Business School

Thomas A. Weber

Ecole Polytechnique Federale de Lausanne - MTEI

Date Written: April 25, 2010

Abstract

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 optimizes and identifies the decision problem, is illustrated for the problem of optimal debt settlement in the credit-card industry.

Keywords: B-Splines, Monotone Approximation, Nonparametric/Semiparametric Methods, Robust Optimization, Sample-Sparse Environments

JEL Classification: C10, C14

Suggested Citation

Chehrazi, Naveed and Weber, Thomas A., Monotone Approximation of Decision Problems (April 25, 2010). Operations Research, Forthcoming, Available at SSRN: https://ssrn.com/abstract=1324024 or http://dx.doi.org/10.2139/ssrn.1324024

Naveed Chehrazi

Washington University in St. Louis - John M. Olin Business School ( email )

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Thomas A. Weber (Contact Author)

Ecole Polytechnique Federale de Lausanne - MTEI ( email )

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