Effective mutation rate for probabilistic evolutionary design of analogue electrical circuits
The paper represents the approach to evolutionary analogue circuit design on the base of the univariate marginal distribution algorithm. In order to generate a new population the probability distribution is used instead of reproduction operators. It allows us to control evolvability of a population on mesoscopic level. Experimental results obtained have indicated that a high mutation rate increases the success rate, although computational costs are increased too. The effective mutation rate that supplies high success rate and small computational costs is examined for different weightings of the fitness function.