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

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Cloud Computing and Security (ICCCS 2018)

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Abstract

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.

This work is supported by the National Natural Science Foundation of China (Grant No. 11661009), the Guangxi Science Fund for Distinguished Young Scholars (No. 2015GXNSFGA139001), and the Guangxi Natural Science Key Fund (No. 2017GXNSFDA198046).

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Authors and Affiliations

  1. College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi, People’s Republic of China

    Wujie Hu & Gonglin Yuan

  2. College of Mathematics and Science, Dalian University of Technology, Dalian, Liaoning, 116024, People’s Republic of China

    Xiaoliang Wang

Authors
  1. Xiaoliang Wang
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  2. Wujie Hu
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  3. Gonglin Yuan
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Corresponding author

Correspondence to Gonglin Yuan .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Wang, X., Hu, W., Yuan, G. (2018). A Modified Wei-Yao-Liu Conjugate Gradient Algorithm for Two Type Minimization Optimization Models. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11063. Springer, Cham. https://doi.org/10.1007/978-3-030-00006-6_13

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  • DOI: https://doi.org/10.1007/978-3-030-00006-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00005-9

  • Online ISBN: 978-3-030-00006-6

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