No subject

[A.H. Gee]

************** PLEASE DO NOT FORWARD TO OTHER NEWSGOUPS ****************

The following technical report has been placed in the neuroprose 
archives at Ohio State University:

                NEURAL NETWORKS AND COMBINATORIAL
                 OPTIMIZATION PROBLEMS - THE KEY
                     TO A SUCCESSFUL MAPPING

          Andrew Gee, Sreeram Aiyer and Richard Prager

	       Technical Report CUED/F-INFENG/TR 77

	               Cambridge University
		      Engineering Department 
		        Trumpington Street 
		        Cambridge CB2 1PZ 
			     England 


                            Abstract

For several years now there has been much research interest in the use
of Hopfield networks to solve combinatorial optimization problems.
Although initial results were disappointing, it has since been
demonstrated how modified network dynamics and better problem mapping
can greatly improve the solution quality. The aim of this paper is to
build on this progress by presenting a new analytical framework in
which problem mappings can be evaluated without recourse to purely
experimental means. A linearized analysis of the Hopfield network's
dynamics forms the main theory of the paper, followed by a series of
experiments in which some problem mappings are investigated in the
context of these dynamics. In all cases the experimental results are
compatible with the linearized theory, and observed weaknesses in the
mappings are fully explained within the framework. What emerges is a
largely analytical technique for evaluating candidate problem
mappings, without having to resort to the more usual trial and error.

************************ How to obtain a copy ************************

a) Via FTP:

unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
Name: anonymous
Password: neuron
ftp> cd pub/neuroprose
ftp> binary
ftp> get gee.opt_map.ps.Z
ftp> quit
unix> uncompress gee.opt_map.ps.Z
unix> lpr gee.opt_map.ps (or however you print PostScript)

Please note that a couple of the figures in the paper were produced
on an Apple Mac, and the resulting PostScript is not quite standard.
People using an Apple LaserWriter should have no problems though.

b) Via postal mail:

Request a hardcopy from

Andrew Gee,
Speech Laboratory,
Cambridge University Engineering Department, 
Trumpington Street, 
Cambridge CB2 1PZ,
England.

or email me: ahg at eng.cam.ac.uk