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A Modified Wei-Yao-Liu Conjugate Gradient Algorithm for Two Type Minimization Optimization Models

机译:一种修改的魏瑶刘共轭梯度算法,用于两种最小化优化模型

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This paper presents a modified Wei-Yao-Liu conjugate gradient method, which automatically not only has sufficient descent property but also owns trust region property without carrying out any line search technique. The global convergence property for unconstrained optimization problems is satisfied with weak Wolfe-Powell (WWP) line search. Meanwhile, the present method can be extended to solve nonlinear equations problems. Under some mild condition, line search method and project technique, the global convergence is established. Some preliminary numerical tests are presented. The numerical results show its effectiveness.
机译:本文介绍了一个修改的魏瑶刘共轭梯度方法,它自动不仅具有足够的下降性,而且还拥有信任区域属性而不执行任何线路搜索技术。对无约束优化问题的全局融合性质满足于弱Wolfe-Powell(WWP)线搜索。同时,可以扩展本方法以解决非线性方程问题。在一些温和条件下,线路搜索方法和项目技术,建立了全局收敛。提出了一些初步数值测试。数值结果表明了其有效性。

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