Evolutionary algorithm for the Physical Travelling Salesman Problem I want to solve the Physical Travelling Salesman Problem using an evolutionary algorithm.

The objective of the PTSP is to visit the maximum number of waypoints of the map in the minimum number of time steps. 
The map takes the form of a two-dimensional board, where ten waypoints are scattered around and multiple obstacles are present.

Now, I have a way to run random games and create "population" — a list of waypoints in the order we visit them.
I need some idea how to do the crossover. I mean, how to create the next generation.
I saw ideas, but they take in account that each gene contains all the waypoints on the map. (Take a random part from parent1 and take the waypoints that do not appear in parent1 from parent2 in the order they appear in parent2).
What to do in case a gene contains just part of the waypoints?
Have a look at this survey on crossover operators for TSP

It gives you the history of development on this area as well.

List of operators covered:


Partially Mapped Crossover (PMX) [Goldberg, 1985]
Order Crossover (OX) [Davis, 1985] 
Edge Crossover (EX) [Whitley, 1989]
Subtour Exchange Crossover (SXX) [Yamamura, 1992] 
Edge Exchange Crossover (EXX) [Maekawa, 1996]
Edge Assembly Crossover (EAX) [Nagata, 1997]
Partition Crossover (PX) [Whitley, 2009]