Date of Award

Summer 1992

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Electrical & Computer Engineering

Program/Concentration

Electrical Engineering

Committee Director

Mark D. Perdue

Committee Member

David L. Livingston

Committee Member

John W. Stoughton

Committee Member

Derya Alasya

Call Number for Print

Special Collections LD4331.E55F36

Abstract

This thesis presents an application of artificial neural networks in real-time resource reallocation, a methodology used in the implementation of an intelligent interface node in the Computer Integrated Manufacturing (CIM) environment. In particular, the problem is formulated using a Hopfield neural network model. The real-time reallocation problem is mapped into a two-dimensional matrix of neurons similar to Hopfield and Tank's approach to the traveling salesman problem (TSP) . An energy function is formulated in terms of the hard constraints and the solution cost. The interconnection weights and the input biases are determined by the energy function. It is shown through computer simulations that a deterministic Hopfield network does not always provide good solutions for the present problem. However, better solutions are obtained by using the Boltzmann machine with simulated annealing, although the long annealing schedules required for optimal solutions preclude its use for this problem application.

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DOI

10.25777/tavk-km62

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