IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v101y2014icp103-112.html
   My bibliography  Save this article

A new neural network for solving quadratic programming problems with equality and inequality constraints

Author

Listed:
  • Yang, Yongqing
  • Cao, Jinde
  • Xu, Xianyun
  • Hu, Manfeng
  • Gao, Yun

Abstract

A new neural network is proposed in this paper for solving quadratic programming problems with equality and inequality constraints. Comparing with the existing neural networks for solving such problems, the proposed neural network has fewer neurons and an one-layer architecture. The proposed neural network is proven to be global convergence. Furthermore, illustrative examples are given to show the effectiveness of the proposed neural network.

Suggested Citation

  • Yang, Yongqing & Cao, Jinde & Xu, Xianyun & Hu, Manfeng & Gao, Yun, 2014. "A new neural network for solving quadratic programming problems with equality and inequality constraints," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 101(C), pages 103-112.
    • Handle: RePEc:eee:matcom:v:101:y:2014:i:c:p:103-112
    DOI: 10.1016/j.matcom.2014.02.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037847541400055X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2014.02.006?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.

    Citations

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


    Cited by:

    1. Léon Faure & Bastien Mollet & Wolfram Liebermeister & Jean-Loup Faulon, 2023. "A neural-mechanistic hybrid approach improving the predictive power of genome-scale metabolic models," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Sha, Chunlin & Zhao, Hongyong, 2019. "A novel neurodynamic reaction-diffusion model for solving linear variational inequality problems and its application," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 57-75.
    3. Hosseinipour-Mahani, N. & Malek, A., 2016. "A neurodynamic optimization technique based on overestimator and underestimator functions for solving a class of non-convex optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 122(C), pages 20-34.
    4. Wang, Limin & Song, Qiankun, 2020. "Pricing policies for dual-channel supply chain with green investment and sales effort under uncertain demand," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 79-93.
    5. Raja, Muhammad Asif Zahoor & Samar, Raza & Manzar, Muhammad Anwar & Shah, Syed Muslim, 2017. "Design of unsupervised fractional neural network model optimized with interior point algorithm for solving Bagley–Torvik equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 132(C), pages 139-158.

    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:matcom:v:101:y:2014:i:c:p:103-112. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.