Neural networks for solving constrained optimization problems

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Abstract

In this paper we consider several Neural Network architectures for solving constrained optimization problems with inequality constrains. We present a new architecture based on the exact penalty function approach. Simulation results based on SIMULINK® models are given and compared.
Original languageEnglish
Title of host publication4th WSEAS Multi-Conference on Circuits, Systems, Communications and Computers (CSCC'2000), Vouliagmeni (Athens), Greece, July 10-15, 2000
Pages1351-1359
Publication statusPublished - 2000

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    Mladenov, V. M., & Hegt, J. A. (2000). Neural networks for solving constrained optimization problems. In 4th WSEAS Multi-Conference on Circuits, Systems, Communications and Computers (CSCC'2000), Vouliagmeni (Athens), Greece, July 10-15, 2000 (pp. 1351-1359)