Abstract
A similar neural network as Zhang and Constantinides [9] is proposed in this paper for solving nonlinear programming with equality and inequality constraints. We overcome the condition of positive definiteness of Lagrangian Hessian by introducing the Log-Sigmoid (LS) function. Thus the proposed network is simpler than the augmented lagrangian neural network inform and have weaker condition than lagrangian neural network in [9].
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
