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Travelling Salesman Problem



Hi there,

I'm conducting some research into using Genetic Algorithms in a problem
identical to the Travelling salesman problem and came across this list
with interest.

I've conducted some trials using a genetic algorithm software package
called 'Evolver'. The trials were based around varying the number of
destinations and measuring the performance of the software as the number
of destinations (and hence obviously permutations) increases.

The number of destinations used were 25,50,75,100,133. We found that
Evolver performed worse than human performance above 25 destinations. 

I was wondering if anyone had come across any similar research into the
TSP and in particular I'm trying to determine: 

*	Is there a maximum threshold number of destinations that can be
handled by genetic algorithms in the TSP example?

*	Are there any better (& more powerful) genetic algorithm
software packages than 'Evolver' available?

Also rather surprisingly, plotting the total time taken to go round all
the destinations against number of destinations gave a pretty straight
line - (I would have expected a genetic algorithm to give a more random
result). 


Kind Regards

David Bosomworth