Neural Networks are part of a revived technology which has received a lot of hype in recent years. As is
apt to happen in any hyped technology, jargon and predictions make its assimilation and application difficult.
Nevertheless, Neural Networks have found use in a number of areas, working on non-trivial and non-contrived
problems. For example, one net has been trained to "read", translating English text into phoneme sequences. Other
applications of Neural Networks include data base manipulation and the solving of routing and classification types
of optimization problems.
It was their use in optimization that got me involved with Neural Networks. As it turned out, "optimization"
used in this context was somewhat misleading, because while some network configurations could indeed solve certain
kinds of optimization problems, the configuring or "training" of a Neural Network itself is an optimization problem,
and most of the literature which talked about Neural Nets and optimization in the same breath did not speak to my
goal of using Neural Nets to help solve lens optimization problems. I did eventually apply Neural Network to lens
optimization, and I will touch on those results. The application of Neural Nets to the problem of lens selection was
much more successful, and those results will dominate this paper.