A new global optimization method for a symmetric Lipschitz continuous function and the application to searching for a globally optimal partition of a one-dimensional set
type: Item
instance of: scholarly article
title: A new global optimization method for a symmetric Lipschitz continuous function and the application to searching for a globally optimal partition of a one-dimensional set
zbMATH Open document ID: 1377.65067
author: Rudolf Scitovski
published in: Journal of Global Optimization
publication date: 2017-11-02T00:00:00Z
review text: The paper proposes a method for solving a global optimization problem for a symmetric Lipschitz continuous function. The author shows that this problem always has a solution with natural conditions on the data. The proposed method is illustrated by solving a center-based clustering problem with synthetic data. Some numerical experiments are presented by testing the proposed method on the image segmentation problem.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 90C27
Mathematics Subject Classification ID: 90C56
Mathematics Subject Classification ID: 90C57
Mathematics Subject Classification ID: 05E05
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 6802511
zbMATH Keywords: symmetric function
zbMATH Keywords: Lipschitz continuous function
zbMATH Keywords: global optimization
zbMATH Keywords: DIRECT
zbMATH Keywords: SymDIRECT
zbMATH Keywords: DISIMPL
zbMATH Keywords: center-based clustering
zbMATH Keywords: numerical experiment
zbMATH Keywords: image segmentation
describes a project that uses: LGO
describes a project that uses: flexclust
describes a project that uses: SymDIRECT
describes a project that uses: PRMLT
describes a project that uses: DIRECT
MaRDI profile type: Publication
full work available at URL: s10898-017-0510-4
OpenAlex ID: W2594099471
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DOI: 10.1007/S10898-017-0510-4
description: scientific article; zbMATH DE number 6802511