Application of neural networks in optimization problems: a review

Kaveh Ashenayi

doi:10.1117/12.47745

1 March 1991 Application of neural networks in optimization problems: a review

Kaveh Ashenayi

Proceedings Volume 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90; (1991) https://doi.org/10.1117/12.47745
Event: Applications of Optical Engineering: Proceedings of OE/Midwest '90, 1990, Rosemont, IL, United States

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.

Citation Download Citation

Kaveh Ashenayi "Application of neural networks in optimization problems: a review", Proc. SPIE 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90, (1 March 1991); https://doi.org/10.1117/12.47745

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