Curve and surface fitting with splines
Curve and surface fitting with splines
Mathematics of Operations Research
Nonparametric econometrics
Computers and Operations Research
Monotone approximation of aggregation operators using least squares splines
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Operations Research
Testing the Validity of a Demand Model: An Operations Perspective
Manufacturing & Service Operations Management
A practical inventory control policy using operational statistics
Operations Research Letters
Preface to the Special Issue on Computational Economics
Operations Research
Optimal learning for sequential sampling with non-parametric beliefs
Journal of Global Optimization
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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.