Nonmonotone spectral gradient method based on memoryless symmetric rank-one update for large-scale unconstrained optimization
This paper proposes a nonmonotone spectral gradient method for solving large-scale unconstrained optimization problems. The spectral parameter is derived from the eigenvalues of an optimally sized memoryless symmetric rank-one matrix obtained under the measure defined as a ratio of the determinant...
محفوظ في:
المؤلفون الرئيسيون: | Hong, Seng Sim, Chuei, Yee Chen, Wah, June Leong, Jiao, Li |
---|---|
التنسيق: | مقال |
منشور في: |
American Institute of Mathematical Sciences
2021
|
الوصول للمادة أونلاين: | http://psasir.upm.edu.my/id/eprint/94373/ https://www.aimsciences.org/article/doi/10.3934/jimo.2021143 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Scaled memoryless symmetric rank one method for large-scale unconstrained optimization
بواسطة: Leong, Wah June, وآخرون
منشور في: (2008) -
Memoryless modified symmetric rank-one method for large-scale unconstrained optimization
بواسطة: Modarres, Farzin, وآخرون
منشور في: (2009) -
Positive-definite memoryless symmetric rank one method for large-scale unconstrained optimization
بواسطة: Leong, Wah June, وآخرون
منشور في: (2011) -
Memoryless symmetric rank-one method based on modified secant equation for large-scale unconstrained optimization
بواسطة: Khiyabani, Farzin Modarres, وآخرون
منشور في: (2009) -
Scaled memoryless symmetric rank one method for large-scale optimization.
بواسطة: Leong, Wah June, وآخرون
منشور في: (2011)