Indeed, in is purest theoretial form, determining a precisely optimal path in this
type of problem is what computer scientists refer to as "NP complete".
NP means "Non deterministic Polynomial time" and the "complete" part basically
means "forget about finding a solution anytime soon".
One of the most famous problems in this area is the Traveling Salesman
problem, which your cited article references. A seemingly simple problem,
yet it is defined as being "NP-hard". Some of the brightest minds in mathematics
and computing have worked on it and about seven years ago, some researchers
made some in-roads into it with some new algorithms.
Simulated annealing is a powerful technique used in a variety of disciplines
these days. In the mid-80's I first heard of it from colleagues I was working
with at UNSW who were using it to help route very large scale
Though well beyond what Roger would want to do or even need to do
in any practical terms, let alone put in an Excel spreadsheet, it is interesting
to read how techniques such as simulated annealing are still be used today
to find near-optimal solutions to what end up being very complex problems
Thanks for the article reference which is a good read.