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2018•Proceedings of the 2018 7th International Conference on Energy and Environmental Protection (ICEEP 2018)Open access

A Variant Hybrid Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization

Zhijun Luo, Lirong Wang, Guohua Chen

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Abstract

In this paper, we have presented a new hybrid conjugate gradient algorithm for solving unconstrained optimization problems.The parameter β is a convex combination of the PRP and FR conjugate gradient methods.Under general wolfe line search conditions, we proved the global convergence of the algorithm.The numerical results show that the proposed methods are effective.

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In this paper, we have presented a new hybrid conjugate gradient algorithm for solving unconstrained optimization problems.The parameter β is a convex combination of the PRP and FR conjugate gradient methods.Under general wolfe line search conditions, we proved the global convergence of the algorithm.The numerical results show that the proposed methods are effective.

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Available abstract

In this paper, we have presented a new hybrid conjugate gradient algorithm for solving unconstrained optimization problems.The parameter β is a convex combination of the PRP and FR conjugate gradient methods.Under general wolfe line search conditions, we proved the global convergence of the algorithm.The numerical results show that the proposed methods are effective.

Key concepts: Conjugate gradient method, Scale (ratio), Computer science, Algorithm, Conjugate, Nonlinear conjugate gradient method, Mathematical optimization, Mathematics

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