基于无记忆 BFGS 方向和 Dai-Liao 共轭条件的两种高效光谱混合 CG 方法

IF 1.4 3区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Pengjie Liu, Zihang Yuan, Yue Zhuo, Hu Shao
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引用次数: 0

摘要

谱共轭梯度法(CG)是解决无约束优化问题的有效方法之一。在这项工作中,我们引入了一种复合混合共轭梯度法参数,它是一种共...
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two efficient spectral hybrid CG methods based on memoryless BFGS direction and Dai–Liao conjugacy condition
The spectral conjugate gradient (CG) method is one of the effective methods for solving unconstrained optimization problems. In this work, we introduce a composite hybrid CG parameter which is a co...
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来源期刊
Optimization Methods & Software
Optimization Methods & Software 工程技术-计算机:软件工程
CiteScore
4.50
自引率
0.00%
发文量
40
审稿时长
7 months
期刊介绍: Optimization Methods and Software publishes refereed papers on the latest developments in the theory and realization of optimization methods, with particular emphasis on the interface between software development and algorithm design. Topics include: Theory, implementation and performance evaluation of algorithms and computer codes for linear, nonlinear, discrete, stochastic optimization and optimal control. This includes in particular conic, semi-definite, mixed integer, network, non-smooth, multi-objective and global optimization by deterministic or nondeterministic algorithms. Algorithms and software for complementarity, variational inequalities and equilibrium problems, and also for solving inverse problems, systems of nonlinear equations and the numerical study of parameter dependent operators. Various aspects of efficient and user-friendly implementations: e.g. automatic differentiation, massively parallel optimization, distributed computing, on-line algorithms, error sensitivity and validity analysis, problem scaling, stopping criteria and symbolic numeric interfaces. Theoretical studies with clear potential for applications and successful applications of specially adapted optimization methods and software to fields like engineering, machine learning, data mining, economics, finance, biology, or medicine. These submissions should not consist solely of the straightforward use of standard optimization techniques.
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