A projection neural-dynamic model for solving fuzzy convex nonlinear programming problems

Document Type : Research Paper

Authors

1 Faculty of Mathematical Sciences, Shahrood University of Technology, P.O. Box 3619995161-316, Tel-Fax No:+98-23-32300235, Shahrood, Iran.

2 Shahrood University of Technology

Abstract

In the proposed manuscript, the solution of the fuzzy nonlinear optimization problems (FNLOPs) is gained
using a projection recurrent neural network (RNN) scheme. Since there is a few research for resolving of FNLOP
by RNN's, we establish a new scheme to solve the problem. By reducing the
original program to an interval problem and then weighting problem, the Karush--Kuhn--Tucker (KKT)
conditions are presented. Moreover, we apply the KKT conditions into a RNN as a efficient tool to solve the problem. Besides, the convergence properties and the
stability analysis of the system model are provided. In the final step, several simulation examples are verified to support the obtained results. Reported results are compared with some other previous neural networks.

Keywords

Main Subjects

References

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Iranian Journal of Fuzzy Systems
Volume 21, Issue 3
May and June 2024
Pages 37-63

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