For a set of points P, connected by weighted edges (distances) I need a path through all points while minimizing the travel on any edge longer than X
Create a graph from the airport coordinates where edges have the haversine distance as weights.  Since the graph is a metric graph, you can apply Christofides algorithm.  This algorithm is a $\frac 3 2$-appoximation, which means that it gives a solution which is not worse than 50% longer than the optimal.
However, since you want to also minimize the number of long edges, you can remove all edges that are longer than you would like, but you now have a non-metric graph (it does no longer satisfy the triangle inequality).
One related problem is the Bottleneck traveling salesman problem, in which you want to find a Hamiltonian path that minimizes the longest edge.  Since your original graph is a metric graph, you can apply the 2-approximation to get an algorithm in which the longest edge is not more than twice possible.

Since you seem to be set on using genetic algorithm, you can consider using both of these algorithms for seeding the initial pool for the GA.  Run both algorithms many times to get many different solutions (introduce some randomness), and you might have a very good starting pool.