Title
Least Squares Approximation to the Distribution of Project Completion Times with Gaussian Uncertainty
Abstract
AbstractThis paper is motivated by the following question: How to construct good approximation for the distribution of the solution value to linear optimization problem when the random objective coefficients follow a multivariate normal distribution? Using Stein’s Identity, we show that the least squares normal approximation of the random optimal value can be computed by estimating the persistency values of the corresponding optimization problem. We further extend our method to construct a least squares quadratic estimator to improve the accuracy of the approximation; in particular, to capture the skewness of the objective. Computational studies show that the new approach provides more accurate estimates of the distributions of project completion times compared to existing methods.
Year
DOI
Venue
2016
10.1287/opre.2016.1528
Periodicals
Keywords
Field
DocType
distribution approximation,persistency,Stein's identity,project management,statistical timing analysis
Least squares,Mathematical optimization,Skewness,Quadratic equation,Gaussian,Multivariate normal distribution,Non-linear least squares,Optimization problem,Mathematics,Estimator
Journal
Volume
Issue
ISSN
64
6
0030-364X
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Zhichao Zheng1583.59
Karthik Natarajan240731.52
Chung-Piaw Teo360.77