Solving the unconstrained optimization problem by a variable neighborhood search

被引：19

作者：

Toksari, M. Duran ^{[1
]}

Guner, Ertan

机构：

[1] Erciyes Univ, Fac Engn, Dept Ind Engn, Kayseri, Turkey

[2] Gazi Univ, Fac Engn & Architecture, Dept Ind Engn, Ankara, Turkey

来源：

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS | 2007年 / 328卷 / 02期

关键词：

variable neighborhood search; global optimization; meta-heuristics;

D O I：

10.1016/j.jmaa.2006.06.025

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper presents variable neighborhood search (VNS) for the problem of finding the global minimum of a nonconvex function. The variable neighborhood search, which changes systematically neighborhood structures in the search for finding a better solution, is used to guide a set of standard improvement heuristics. This algorithm was tested on some standard test functions, and successful results were obtained. Its performance was compared with the other algorithms, and observed to be better. (c) 2006 Elsevier Inc. All rights reserved.

引用

页码：1178 / 1187

页数：10

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