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Proceedings Paper

Application of neural networks in optimization problems: a review
Author(s): Kaveh Ashenayi
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Paper Abstract

In the recent past neural networks have been used in a variety of applications. The wide spectrum of applications has required invention of new architectures as well as improving existing architectures. This paper reviews some of different neural network architectures and their applications in optimization problems. The paper is divided into three primary sections: 1) a brief review of the type of problems that are suitable for neural networks 2) a brief description of some of the more commonly used neural network models and 3) a quick glance at application of Hopfield network to optimization problems. The first part will provide a quick glance at the two class of problems best suited for neural networks. The second part will briefly review various networks currently in use today. The application section will provide examples describing use of Hopfield network for solving economic load dispatch and linear programming problems. The paper also includes an extensive bibliography. 1.

Paper Details

Date Published: 1 March 1991
PDF: 12 pages
Proc. SPIE 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90, (1 March 1991); doi: 10.1117/12.47745
Show Author Affiliations
Kaveh Ashenayi, Univ. of Tulsa (United States)


Published in SPIE Proceedings Vol. 1396:
Applications of Optical Engineering: Proceedings of OE/Midwest '90
Rudolph P. Guzik; Hans E. Eppinger; Richard E. Gillespie; Mary Kathryn Dubiel; James E. Pearson, Editor(s)

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