Response Surface Optimization when Experimental Factors are Subject to Costs and Constraints
作者:
NelsonB. Heller,
GlennE. Staats,
期刊:
Technometrics
(Taylor Available online 1973)
卷期:
Volume 15,
issue 1
页码: 113-123
ISSN:0040-1706
年代: 1973
DOI:10.1080/00401706.1973.10489015
出版商: Taylor & Francis Group
关键词: Response Surface Optimization;Gradient Search;Steepest Ascent;Constrained Experimental Optimization;Cost Models for Experimental Optimization Variables;Scale-Invariant Search Techniques
数据来源: Taylor
摘要:
This paper deals with problems of response surface optimization in which the control variables and responses are subject to costs and constraints. Relationships between control variables and the cost or constraint functions are treated as additional response surfaces if explicit algebraic models are unavailable. Optimization methods are suggested which are based on gradient search and nonlinear programming techniques. To assure operating conditions within the specified constraint set a method based on feasible directions is used to control the search pattern. A scale-invariant gradient search method is suggested. Because it leads to an economical path to the maximum point the method has been dubbed “cheapest ascent.” The selection of measurement scales for the control variables is also discussed.
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