The effect of selection on the development of mutational robustness

This paper investigates the role of selection in the acquisition of mutational robustness for two test problems: rONEMAX and SAW. Three different selection methods: tournament, fitness proportionate, and ranking, were implemented in a geerational genetic algorithm and applied to both problems. The effect of altering the selection pressure for the tournament selection method was investigated by varying the tournament size. For the rONEMAX problem the tournament and ranking selection based algorithms found optimal solutions which were significantly more robust to point mutation than those found by either the fitness proportionate selection algorithm or random sampling of the optimal solution space. Altering the selection pressure had no significant effect on the robustness of the solutions located by tournament selection algorithm for the rONEMAX problem. For the SAW problem, however, tournament selection with a tournament size of four found solutions which were significantly more robust than those located by larger tournament sizes. For the majority of the problem variants explored here the tournament and ranking selection methods proved more effective at locating robust optimal solutions than fitness proportionate selection.