A integral filter algorithm for unconstrained global optimization

doi:10.1016/j.amc.2006.05.147

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A integral filter algorithm for unconstrained global optimization

2007-01-01

PRE

Yongjian Yang *

DU Xue-wu

Mingming Li

DOI：10.1016/j.amc.2006.05.147

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Abstract

En 中文

In this paper, making use of an integral inequality, a necessary and sufficient condition is given for a point to be a global minimizer. Based on the integral inequality, a novel integral-form algorithm is proposed for unconstrained global optimization. It is different from the other deterministic global search algorithm. Under mild conditions it is proved that, in theory, a global minimizer of the objective function can be certainly found by the presented algorithm. In order to indicate the efficiency and reliability of the method, four numerical examples are reported. (C) 2006 Elsevier Inc. All rights reserved.

Keywords:

global optimization

integral

branch and bound

local search algorithm