his article presents a novel neural network (NN) based on NCP function for solving nonconvex nonlinear optimization (NCNO) problem subject to nonlinear inequality constraints. We first apply the p-power convexification ...

This paper presents a neural network based on NCP function to solve a class of nonconvex nonlinear optimization (NCNO) problems. The proposed neural network is a gradient model, which is constructed with an NCP

function ...

in the sense of Lyapunov, globally convergent, globally asymptotically stable, and globally exponentially stable. Also, we show that, our new neurodynamic model is effective to solve the nonconvex optimization problems. Moreover, since monotonicity is a special...

The present scientific attempt is devoted to investigating the fuzzy nonconvex optimization problems (NCOPs) utilizing the concepts of recurrent neural networks (RNNs). To the best of our knowledge, this paper is the first study on finding a...