A GLOBALLY CONVERGENT MODIFIED MULTIVARIATE VERSION OF THE METHOD OF MOVING ASYMPTOTES

被引：2
|
作者：
Guessab, Allal [1 ]
Driouch, Abderrazak [1 ]
机构：
[1] Univ Pau & Pays Adour, E2S UPPA, CNRS, LMAP, F-64000 Pau, France
来源：
APPLICABLE ANALYSIS AND DISCRETE MATHEMATICS | 2021年 / 15卷 / 02期
关键词：
Non-convex; Non Linear Optimization; Global Convergence; Method of Moving Asymptotes;
D O I：
10.2298/AADM190325033G
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we introduce an extension of our previous paper, A globally convergent version to the Method of Moving Asymptotes, in a multivariate setting. The proposed multivariate version is a globally convergent result for a new method, which consists iteratively of the solution of a modified version of the method of moving asymptotes. It is shown that the algorithm generated has some desirable properties. We state the conditions under which the present method is guaranteed to converge geometrically. The resulting algorithms are tested numerically and compared with several well-known methods.
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页码：519 / 535
页数：17
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