The combination of local optimisation heuristics and genetic algorithms has been shown to be an effective approach for finding near-optimum solutions to the travelling salesman problem (TSP). In problem domains where the problem can be represented geometrically, such as networks and chemical structures, the combination of local optimisation operators and phenotype genetic operators has also been an effective approach. This paper evaluates the combination of local optimisation heuristics and phenotype genetic operators when applied to the TSP. The local optimisation heuristics reduce the search domain, while the phenotype genetic operators eliminate the creation of invalid tours and also assist the generation of suboptimal schema. The implementation of the genetic algorithm is described and results presented.