Abstract
In this paper, a neural network model for solving convex nonlinear programming problems is investigated based on the Fischer-Burmeister function and steepest descent method. The proposed neural network is proved to be stable in the sense of Lyapunov and can converge to an optimal solution of the original optimization problem. An example shows the effectiveness of the proposed neural network model.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Zhang, Y., Wang, J.: A Dual Neural Network for Convex Quadratic Programming Subject to Linear Equality and Inequality Constraints. Physics Letters A 298, 271–278 (2002)
Tao, Q., Cao, J., Xue, M., Qiao, H.: A High Performance Neural Network for Solving Nonlinear Programming Problems with Hybrid Constraints. Physics Letters A 288, 88–94 (2001)
Liu, Q., Cao, J., Xia, Y.: A Delayed Neural Network for Solving Linear Projection Equations and Its Analysis. IEEE Transactions on Neural Networks 16, 834–843 (2005)
Liu, Q., Wang, J., Cao, J.: A Delayed Lagrangian Network for Solving Quadratic Programming Problems with Equality Constraints. In: Wang, J., Yi, Z., Żurada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol. 3971, pp. 369–378. Springer, Heidelberg (2006)
Xia, Y., Feng, G.: A Modified Neural Network for Quadratic Programming with Real-Time Applications. Neural Information Processing-Letter and Reviews 3, 69–75 (2004)
Kennedy, M.P., Chua, L.O.: Neural Networks for Nonlinear Programming. IEEE Trans. Circuits Syst. 35, 554–562 (1988)
Chen, K.Z., Leung, Y., Leung, K.S., Gao, X.B.: A Neural Network for Solving Nonlinear Programming Problem. Neural Computing and Applications 11, 103–111 (2002)
Xia, Y., Wang, J.: A Recurrent Neural Networks for Nonlinear Convex Optimization Subject to Nonlinear Inequality Constraints. IEEE Trans. Circuits Syst.-I 51, 1385–1394 (2004)
Gao, X.B.: A Novel Neural Network for Nonlinear Convex Programming. IEEE Trans. Neural Networks 15, 613–621 (2004)
Cao, J., Li, X.: Stability in Delayed Cohen-Grossberg Neural Networks: LMI Optimization Approach. Physica D: Nonlinear Phenomena 212, 54–65 (2005)
Effati, S., Nazemi, A.R.: Neural Network Models and Its Application for Solving Linear and Quadratic Programming Problems. Applied mathematics and Computation 172, 305–331 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, Y., Xu, X., Zhu, D. (2006). The Neural Network for Solving Convex Nonlinear Programming Problem. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_62
Download citation
DOI: https://doi.org/10.1007/11816157_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
Online ISBN: 978-3-540-37273-8
eBook Packages: Computer ScienceComputer Science (R0)