Analysis and Development of Surrogate Assisted Derivative-free Optimization Algorithms
Date Issued
2009
Date
2009
Author(s)
Lin, Yu-Ting
Abstract
This paper investigates a method for solving optimization problems to find the minimizers of a function. To this end, the algorithm derived from image process generates a surrogate surface to pick initial points and then estimates the minimizers. Results indicated that the surrogate surface is similar to the real one. The minimal points can be correctly estimated in diversified cases. The algorithm is adaptive on constructing a surrogate surface preserving the main feature of the real one. Moreover, this paper gives complete convergence analysis on the Adoptive Search Regions Method and states that the minimizer of a function can be estimated by specific surrogate surfaces.
Subjects
optimization
derivative-free
surrogate
convergence analysis
ASRM
Framelet
image inpainting
pointwise converge
Type
thesis
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