IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v387y2020ics0096300320301442.html
   My bibliography  Save this article

A modulus-based nonmonotone line search method for nonlinear complementarity problems

Author

Listed:
  • Zhang, Xu
  • Peng, Zheng

Abstract

A modulus-based nonmonotone line search method is proposed for nonlinear complementarity problem. The considered problem is first reformulated to a nonsmooth nonlinear system based on the modulus-based decomposition. Then a nonmonotone line search method using simulated annealing rule is generalized to solve the resulting system. The global convergence of the proposed method is established under some suitable assumptions. Preliminary numerical experiments show that, compared with some existing methods, the proposed method is feasible and effective.

Suggested Citation

  • Zhang, Xu & Peng, Zheng, 2020. "A modulus-based nonmonotone line search method for nonlinear complementarity problems," Applied Mathematics and Computation, Elsevier, vol. 387(C).
    • Handle: RePEc:eee:apmaco:v:387:y:2020:i:c:s0096300320301442
    DOI: 10.1016/j.amc.2020.125175
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300320301442
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2020.125175?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wen, Baolian & Zheng, Hua & Li, Wen & Peng, Xiaofei, 2018. "The relaxation modulus-based matrix splitting iteration method for solving linear complementarity problems of positive definite matrices," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 349-357.
    2. Jein-Shan Chen, 2007. "On Some Ncp-Functions Based On The Generalized Fischer–Burmeister Function," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 24(03), pages 401-420.
    3. Yuan, Xiao-ming, 2007. "The prediction-correction approach to nonlinear complementarity problems," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1357-1370, February.
    4. Changfeng Ma, 2010. "A new smoothing and regularization Newton method for P 0 -NCP," Journal of Global Optimization, Springer, vol. 48(2), pages 241-261, October.
    5. Wen-Li Dong & Xing Li & Zheng Peng, 2019. "A Simulated Annealing-Based Barzilai–Borwein Gradient Method for Unconstrained Optimization Problems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(04), pages 1-12, August.
    6. A. Bnouhachem & X. M. Yuan, 2007. "Extended LQP Method for Monotone Nonlinear Complementarity Problems," Journal of Optimization Theory and Applications, Springer, vol. 135(3), pages 343-353, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Baohua Huang & Wen Li, 2023. "A smoothing Newton method based on the modulus equation for a class of weakly nonlinear complementarity problems," Computational Optimization and Applications, Springer, vol. 86(1), pages 345-381, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zheng, Hua & Vong, Seakweng & Liu, Ling, 2019. "A direct preconditioned modulus-based iteration method for solving nonlinear complementarity problems of H-matrices," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 396-405.
    2. Sanja Rapajić & Zoltan Papp, 2017. "A nonmonotone Jacobian smoothing inexact Newton method for NCP," Computational Optimization and Applications, Springer, vol. 66(3), pages 507-532, April.
    3. Zheng, Hua & Vong, Seakweng, 2021. "On the modulus-based successive overrelaxation iteration method for horizontal linear complementarity problems arising from hydrodynamic lubrication," Applied Mathematics and Computation, Elsevier, vol. 402(C).
    4. Jingyong Tang & Jinchuan Zhou, 2021. "Quadratic convergence analysis of a nonmonotone Levenberg–Marquardt type method for the weighted nonlinear complementarity problem," Computational Optimization and Applications, Springer, vol. 80(1), pages 213-244, September.
    5. Tang, Jingyong & Zhou, Jinchuan & Fang, Liang, 2015. "A non-monotone regularization Newton method for the second-order cone complementarity problem," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 743-756.
    6. Pin-Bo Chen & Gui-Hua Lin & Xide Zhu & Fusheng Bai, 2021. "Smoothing Newton method for nonsmooth second-order cone complementarity problems with application to electric power markets," Journal of Global Optimization, Springer, vol. 80(3), pages 635-659, July.
    7. Hua Zheng & Ling Liu, 2019. "The Sign-Based Methods for Solving a Class of Nonlinear Complementarity Problems," Journal of Optimization Theory and Applications, Springer, vol. 180(2), pages 480-499, February.
    8. M. Li & L. Z. Liao & X. M. Yuan, 2009. "Proximal Point Algorithms for General Variational Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 142(1), pages 125-145, July.
    9. Zhizhi Li & Huai Zhang & Le Ou-Yang, 2021. "The selection of the optimal parameter in the modulus-based matrix splitting algorithm for linear complementarity problems," Computational Optimization and Applications, Springer, vol. 80(2), pages 617-638, November.
    10. Xuebin Wang & Changfeng Ma & Meiyan Li, 2011. "A globally and superlinearly convergent quasi-Newton method for general box constrained variational inequalities without smoothing approximation," Journal of Global Optimization, Springer, vol. 50(4), pages 675-694, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:387:y:2020:i:c:s0096300320301442. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.