Mathematica Eterna
Libre accès

Abstrait

A Memory Gradient Method under new Nonmonotone Line Search Technique for Unconstrained Optimization

Ke Su and Zixing Rong

In this paper, we combine a new Memory gradient methods with a nonmonotone line search technique and we obtain a new algorithm. which perform efficiently both in theoretical and numerical results, what is more, we prove the global convergence of the algorithm under mild conditions, in the end Our numerical results show that the proposed method is efficient for given standard test problems if we choose a good parameter included in the method, furthermore, there are some advantages In theory.