Please use this identifier to cite or link to this item:
Title: Two-stage computing budget allocation approach for response surface method
Authors: PENG JI
Keywords: Computing Budget Allocation, Experimental Design, Response Surface Methodology, Simulation Optimization
Issue Date: 18-Jan-2006
Citation: PENG JI (2006-01-18). Two-stage computing budget allocation approach for response surface method. ScholarBank@NUS Repository.
Abstract: Response Surface Methodology (RSM) is one of the main statistical approaches to search for the input combination that optimizes the simulation output. In the early stages of RSM, the steepest ascent method, which is scale-dependent, is used. Recently, a novel technique is proposed to identify the next design point with a scale-independent search direction and a possible step size. In this thesis, we improve this technique by considering the more realistic case where there are computing budget constraints, and look into the important question of experimental design. We propose a two-stage computing budget allocation approach, and do several numerical experiments to compare it with the traditional factorial designs which allocate budget equally to each design point. The results show that our technique outperforms the traditional equal allocation when the system noise is large.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
PengJ.pdf1.27 MBAdobe PDF



Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.