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Proceedings Paper

Task scheduling neural networks
Author(s): William J. Wolfe
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Paper Abstract

In this paper a neural network approach to a particular class of scheduling problems is described. It uses a `k-cluster' network to enforce a non-preemptive time duration constraint and a `subset-sum' network to generate feasible schedules with a balanced load distribution. The two networks are super-imposed and the interactive nature of the parallel distributed processing inherent to Hopfield-Style neural networks negotiates the multiple constraint satisfaction requirements.

Paper Details

Date Published: 1 February 1994
PDF: 7 pages
Proc. SPIE 2058, Mobile Robots VIII, (1 February 1994); doi: 10.1117/12.167509
Show Author Affiliations
William J. Wolfe, Univ. of Colorado/Denver (United States)

Published in SPIE Proceedings Vol. 2058:
Mobile Robots VIII
William J. Wolfe; Wendell H. Chun, Editor(s)

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