Monotone Approximation of Decision Problems

• 成果类型: Article
• 署名作者: Chehrazi, Naveed; Weber, Thomas A.
• 署名单位: Stanford University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.1100.0814
• 发表日期: 2010
• 页码: 1158-1177
• 关键词: spline interpolation; optimization; identification; POLYNOMIALS; ambiguity

摘要

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.