  In this paper, we will propose convex layers to the Traveling Salesman
Problem (TSP). Firstly, we will focus on human performance on the TSP.
Experimental data shows that untrained humans appear to have the ability to
perform well in the TSP. On the other hand, experimental data also supports the
hypothesis of convex hull i.e. human relies on convex hull to search for the
optimal tour for the TSP. Secondly, from the paper published by Bonabeau,
Dorigo and Theraulaz, social insect behavior would be able to help in some of
the optimizing problems, especially the TSP. Thus, we propose convex layers to
the TSP based on the argument that, by the analogy to the social insect
behavior, untrained humans' cognition should be able to help in the TSP.
Lastly, we will use Tour Improvement algorithms on convex layers to search for
an optimal tour for a 13-cities problem to demonstrate the idea.
