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A New Hybrid Three-Term Conjugate Gradient Algorithm for Large-Scale Unconstrained Problems
| Content Provider | MDPI |
|---|---|
| Author | Tian, Qi Wang, Xiaoliang Pang, Liping Zhang, Mingkun Meng, Fanyun |
| Copyright Year | 2021 |
| Description | Three-term conjugate gradient methods have attracted much attention for large-scale unconstrained problems in recent years, since they have attractive practical factors such as simple computation, low memory requirement, better descent property and strong global convergence property. In this paper, a hybrid three-term conjugate gradient algorithm is proposed and it owns a sufficient descent property, independent of any line search technique. Under some mild conditions, the proposed method is globally convergent for uniformly convex objective functions. Meanwhile, by using the modified secant equation, the proposed method is also global convergence without convexity assumption on the objective function. Numerical results also indicate that the proposed algorithm is more efficient and reliable than the other methods for the testing problems. |
| Starting Page | 1353 |
| e-ISSN | 22277390 |
| DOI | 10.3390/math9121353 |
| Journal | Mathematics |
| Issue Number | 12 |
| Volume Number | 9 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-06-11 |
| Access Restriction | Open |
| Subject Keyword | Mathematics Industrial Engineering Three-term Conjugate Gradient Method Sufficient Descent Property Secant Equation Conjugate Condition Global Convergence Acceleration Strategy |
| Content Type | Text |
| Resource Type | Article |
