Tuning Genetic Algorithms for Problems Including Neutral Networks-A More Complex Case : The Terraced NK Problem -

Neutral networks, which occur in fitness landscapes containing neighboring points of equal fitness, have attracted much research interest in recent years. In a recent paper [12], we have shown that, in the case of a very simple test function, the mutation rate of a genetic algorithm is an important factor for improving the speed at which a population moves along a neutral network. Our results also suggested that a variable mutation rate strategy is beneficial for fast and stable genetic search. In this work, we conduct a series of computer simulations with a more complex test function, the terraced NK landscape, in order to investigate whether our previous results generalize to this more complex case. Two types of GA were used. One is the standard GA, where the mutation rate is constant, and the other is the operon-GA, whose effective mutation rate at each locus changes independently according to the history of the genetic search. It is found that the variable mutation rate strategy is also beneficial with this more complex test function, and that these benefits increase as the fitness landscape becomes more rugged.