A new subspace minimization conjugate gradient method based on tensor model for unconstrained optimization

作者：Wang, Ting; Liu, Zexian^*; Liu, Hongwei

来源：International Journal of Computer Mathematics, 2019, 96(10): 1924-1942.

DOI：10.1080/00207160.2018.1542136

• Conjugate gradient method
• tensor model
• subspace technique
• non-monotone line search
• unconstrained optimizaiton

A new subspace minimization conjugate gradient method based on tensor model is proposed and analysed. If the objective function is close to a quadratic, we construct a quadratic approximation model in a two-dimensional subspace to generate the search direction; otherwise, we construct a tensor model. It is remarkable that the search direction satisfies the sufficient descent property. We prove the global convergence of the proposed method under mild assumptions. Numerical comparisons are given with well-known CGOPT and CG_DESCENT and show that the proposed algorithm is very promising.

• 出版日期2019-10-3
• 单位西安电子科技大学; 贺州学院