Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10174
Title: Behavioral estimation of mathematical programming objective function coefficients
Authors: Troutt, MD
Pang, WK
Hou, SH
Keywords: Decisional regret
Inverse optimization
Parameter estimation
Production-planning costs
Target-mode agreement criterion
Issue Date: 2006
Publisher: Institute for Operations Research and the Management Sciences
Source: Management science, 2006, v. 52, no. 3, p. 422-434 How to cite?
Journal: Management science 
Abstract: We propose a parameter estimation method based on what we call the minimum decisional regret principle. We focus on mathematical programming models with objective functions that depend linearly on costs or other parameters. The approach is illustrated for cost estimation in production planning using linear programming models. The method uses past planning data to estimate costs that are otherwise difficult to estimate. We define a monetary measure of distance between observed plans and optimal ones, called decisional regret. The proposed estimation algorithm finds parameter values for which the associated optimal plans are as near as possible to the observed ones on average. Such techniques may be called behavioral estimation because they are based on the observed planning or decision-making behavior of managers or firms. Two numerical illustrations are given. A supporting hyperplane algorithm is used to solve the estimation model. A method is proposed for obtaining range estimates of the parameters when multiple alternative estimates exist. We also propose a new validation approach for this estimation principle, which we call the target-mode agreement criterion.
URI: http://hdl.handle.net/10397/10174
ISSN: 0025-1909
EISSN: 1526-5501
DOI: 10.1287/mnsc.1050.0445
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