How to Use the Scuba Diving Metaphor to Solve Problems with Neutrality?

We proposed a new search heuristic using the scuba diving metaphor. This approach is based on the concept of evolvability and tends to exploit neutrality which exists in many real-world problems. Despite the fact that natural evolution does not directly select for evolvability, the basic idea behind the scuba search heuristic is to explicitly push evolvability to increase. A comparative study of the scuba algorithm and standard local search heuristics has shown the advantage and the limitation of the scuba search. In order to tune neutrality, we use the N Kq fitness landscapes and a family of travelling salesman problems (TSP) where cities are randomly placed on a lattice and where travel distance between cities is computed with the Manhattan metric. In this last problem the amount of neutrality varies with the city concentration on the grid ; assuming the concentration below one, this TSP reasonably remains a NP-hard problem.