A conjugate gradient method for solving unconstrained optimization problems
For the conjugate gradient method to solve the unconstrained optimization problem, given a new interval method to obtain the direction parameters, and a new conjugate gradient algorithm is designed. The global convergence of the algorithm under the Armijo step search is also discussed. Making use of MATLAB to programming, and numerical examples’ results show that the new algorithm is more efficient than the FR,PR,HS conjugate gradient algorithm based on Armijo step search.
Authors
- Bing Yan (ORCID: https://orcid.org/0000-0002-7970-6764)
- Benyu Wang
- Biao Guo (ORCID: https://orcid.org/0000-0002-4366-0848)
- Liangbo Hu
- Haoyang Li (ORCID: https://orcid.org/0000-0001-9786-2536)
- Chao Zhang (ORCID: https://orcid.org/0000-0002-1018-4144)
- Hongwei Zhang (ORCID: https://orcid.org/0009-0000-3793-9968)
- Shuangye Yang
Institutions
- Beijing Agricultural Machinery Research Institute (CN)
- Kelun Group (China) (CN)
- China National Petroleum Corporation (China) (CN)
Publication Details
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1109/icmsp64464.2024.10867051
- Citations
- 1
- Primary Topic
- Advanced Optimization Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 0.73