I'm building a genetic algorithm to tackle the traveling salesman problem.  Unfortunately, I hit peaks that can sustain for over a thousand generations before mutating out of them and getting better results.  What crossover and mutation operators generally do well in this case?
If your problem is that peaks remain for over one thousand generations, then the problem might not be with the crossover and mutation operators.  You might not be introducing or keeping enough variation to your population: I would examine the proportions of crossovers, of mutations, and of survivors from one generation to the next, and possibly raise the proportion of mutations.
Suggested GA operators for a TSP problem?