Extra updates for the BFGS method

M. Al-Baali*

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

16 اقتباسات (Scopus)

ملخص

This paper considers employing extra updates for the BFGS method for unconstrained optimization. The usual BFGS Hessian is updated a number of times, depending on the information of the first order derivatives, to obtain a new Hessian approximation at each iteration. Two approaches are proposed. One of them has the same properties of global and superlinear convergence on convex functions the BFGS method has, and another has the same property of quadratic termination without exact line searches that the symmetric rank-one method has. The new algorithms attempt to combine the best features of certain methods which are intended for either parallel computation or large scale optimization. It is concluded that some new algorithms are competitive with the standard BFGS method.

اللغة الأصليةEnglish
الصفحات (من إلى)159-179
عدد الصفحات21
دوريةOptimization Methods and Software
مستوى الصوت13
رقم الإصدار3
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2000

ASJC Scopus subject areas

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