Moving Least Squares regression for high dimensional simulation metamodeling

Author

Salemi, Peter ; Nelson, Barry L. ; Staum, Jeremy

Author_Institution

Dept. of Ind. Eng. & Manage. Sci., Northwestern Univ., Evanston, IL, USA

fYear

2012

fDate

9-12 Dec. 2012

Firstpage

1

Lastpage

12

Abstract

Interpolation and smoothing methods form the basis of simulation metamodeling. In high dimensional metamodeling problems, larger numbers of design points are needed to build an accurate metamodel. This paper introduces a procedure to implement a smoothing method called Moving Least Squares regression in high dimensional metamodeling problems with a large number of design points. We test the procedure with two queueing examples: a multi-product M/G/1 queue and a multi-product Jackson network.

Keywords

interpolation; least squares approximations; modelling; queueing theory; regression analysis; simulation; smoothing methods; design points; high dimensional simulation metamodeling problems; interpolation methods; moving least squares regression; multiproduct Jackson network; multiproduct M/G/1 queue; smoothing methods; Bandwidth; Kernel; Least squares approximation; Metamodeling; Polynomials; Predictive models; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference (WSC), Proceedings of the 2012 Winter

Conference_Location

Berlin

ISSN

0891-7736

Print_ISBN

978-1-4673-4779-2

Electronic_ISBN

0891-7736

Type

conf

DOI

10.1109/WSC.2012.6465122

Filename

6465122