Two minimal positive bases based direct search conjugate gradient methods for computationally expensive functions |
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Authors: | Qunfeng Liu |
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Institution: | (1) Department of Informatics, University of Bergen, Bergen, Norway |
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Abstract: | Positive basis is an important concept in direct search methods. Although any positive basis can ensure the convergence in
theory, the maximum positive bases are often used to construct direct search algorithms. In this paper, two direct search
methods for computational expensive functions are proposed based on the minimal positive bases. The Coope–Price’s frame-based
direct search framework is employed to insure convergence. PRP+ method and a recently developed descent conjugate gradient
method are employed respectively to accelerate convergence. The data profiles and the performance profiles of the numerical
experiments show that the proposed methods are effective for computational expensive functions. |
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Keywords: | |
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