Stochastic trust region gradient-free method (strong) - A new response-surface-based algorithm in simulation optimization

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - Winter Simulation Conference
Pages346-354
Publication statusPublished - 2007
Externally publishedYes

Publication series

Name
ISSN (Print)0891-7736

Conference

Title2007 Winter Simulation Conference (WSC'07)
PlaceUnited States
CityWashington
Period9 - 12 December 2007

Abstract

Response Surface Methodology (RSM) is a metamodelbased optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting to explore the entire parameter space directly. This method has been widely used in simulation optimization. However, RSM has two significant shortcomings: Firstly, it is not automated. Human involvements are usually required in the search process. Secondly, RSM is heuristic without convergence guarantee. This paper proposes Stochastic Trust Region Gradient-Free Method (STRONG) for simulation optimization with continuous decision variables to solve these two problems. STRONG combines the traditional RSM framework with the trust region method for deterministic optimization to achieve convergence property and eliminate the requirement of human involvement. Combined with appropriate experimental designs and specifically efficient screening experiments, STRONG has the potential of solving high-dimensional problems efficiently. © 2007 IEEE.

Citation Format(s)

Stochastic trust region gradient-free method (strong) - A new response-surface-based algorithm in simulation optimization. / Chang, Kuo-Hao; Hong, L. Jeff; Wan, Hong.

Proceedings - Winter Simulation Conference. 2007. p. 346-354 4419622.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review