Title of article :
The global and superlinear convergence of a new nonmonotone MBFGS algorithm on convex objective functions
Author/Authors :
Liu، نويسنده , , Liying and Yao، نويسنده , , Shengwei and Wei، نويسنده , , Zengxin، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Pages :
17
From page :
422
To page :
438
Abstract :
In this paper, a new nonmonotone MBFGS algorithm for unconstrained optimization will be proposed. Under some suitable assumptions, the global and superlinear convergence of the new nonmonotone MBFGS algorithm on convex objective functions will be established. Some numerical experiments show that this new nonmonotone MBFGS algorithm is competitive to the MBFGS algorithm and the nonmonotone BFGS algorithm.
Keywords :
Unconstrained optimization , MBFGS algorithm , global convergence , Nonmonotone linesearch , Superlinear convergence
Journal title :
Journal of Computational and Applied Mathematics
Serial Year :
2008
Journal title :
Journal of Computational and Applied Mathematics
Record number :
1554566
Link To Document :
بازگشت