Journal Article10.1080/03052150410001686486
Mode-pursuing sampling method for global optimization on expensive black-box functions
TL;DR: A new global optimization method for black-box functions is proposed, based on a novel mode-pursuing sampling method that systematically generates more sample points in the neighborhood of the function mode while statistically covering the entire search space.
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Abstract: The presence of black-box functions in engineering design, which are usually computation-intensive, demands efficient global optimization methods. This article proposes a new global optimization method for black-box functions. The global optimization method is based on a novel mode-pursuing sampling method that systematically generates more sample points in the neighborhood of the function mode while statistically covering the entire search space. Quadratic regression is performed to detect the region containing the global optimum. The sampling and detection process iterates until the global optimum is obtained. Through intensive testing, this method is found to be effective, efficient, robust, and applicable to both continuous and discontinuous functions. It supports simultaneous computation and applies to both unconstrained and constrained optimization problems. Because it does not call any existing global optimization tool, it can be used as a standalone global optimization method for inexpensive probl...
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Citations
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Trends, Features, and Tests of Common and Recently Introduced Global Optimization Methods
Adel Younis,Zuomin Dong,Jichao Gu,Guangyao Li +3 more
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TL;DR: Global optimization techniques have been used extensively due to their capability in handling complex engineering problems.
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Multi-start Space Reduction (MSSR) surrogate-based global optimization method
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References
•Journal Article
The Design and Analysis of Experiments
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
15.2K
Efficient Global Optimization of Expensive Black-Box Functions
TL;DR: This paper introduces the reader to a response surface methodology that is especially good at modeling the nonlinear, multimodal functions that often occur in engineering and shows how these approximating functions can be used to construct an efficient global optimization algorithm with a credible stopping rule.
•Book
Introduction to Optimum Design
Jasbir S. Arora
- 01 Jul 1989
TL;DR: This fourth edition of the introduction to Optimum Design has been reorganized, rewritten in parts, and enhanced with new material, making the book even more appealing to instructors regardless of course level.
2.8K
Efficient Global Optimization of Expensive Black-Box Functions
Donald R. Jones,Matthias Schonlau,William J. Welch +2 more
TL;DR: This paper introduces the reader to a response surface methodology that is especially good at modeling the nonlinear, multimodal functions that often occur in engineering and shows how these approximating functions can be used to construct an efficient global optimization algorithm with a credible stopping rule.
2.7K
Adaptive Response Surface Method Using Inherited Latin Hypercube Design Points
TL;DR: The improved ARSM is tested using a group of standard test problems and then applied to an engineering design problem, demonstrating strong potential to be a practical global optimization tool for computation-intensive design problems.