Collaborative neurodynamic optimization for solving nonlinear equations.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

A distributed optimization method for solving nonlinear equations with constraints is developed in this paper. The multiple constrained nonlinear equations are converted into an optimization problem and we solve it in a distributed manner. Due to the possible presence of nonconvexity, the converted optimization problem might be a nonconvex optimization problem. To this end, we propose a multi-agent system based on an augmented Lagrangian function and prove that it converges to a locally optimal solution to an optimization problem in the presence of nonconvexity. In addition, a collaborative neurodynamic optimization method is adopted to obtain a globally optimal solution. Three numerical examples are elaborated to illustrate the effectiveness of the main results.

Authors

  • Huimin Guan
    Department of Biomedical Engineering, ShenZhen University, ShenZhen, 518000, China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Kit Ian Kou
    Department of Mathematics, Faculty of Science and Technology, University of Macau, Macau, China.
  • Jinde Cao
  • Leszek Rutkowski
    * Institute of Computational Intelligence, Czestochowa University of Technology, Al. Armii Krajowej 36, 42-200 Czestochowa, Poland.