%0 Journal Article
%A MO Hongqiang
%A ZHU Chunmei
%T Encoding of genetic algorithm for a class of fitness functions
%D 2017
%R 10.11772/j.issn.1001-9081.2017.07.1972
%J Journal of Computer Applications
%P 1972-1976
%V 37
%N 7
%X In the investigation of relationship between the periodicity of fitness function and encoding cardinality, the evaluation of encoding performance using the number of order-1 building blocks is not necessarily established. Focused on this issue, evaluating method of encoding performance of Genetic Algorithm (GA) using Accumulated Escape Probability (AEP) was proposed, and for a class of fitness functions linearly combined of sinusoidal functions whose frequencies are exponential to a positive integer *m*, research on encoding was carried out. Firstly, the general form of the fitness function was given, and the concept of base-*m* encoding was explained. Secondly, the definition of AEP was introduced, and a method was proposed to figure out AEPs. Then the AEPs of the above-mentioned fitness functions under encodings with different encoding bases were compared, and the results showed that, for a fitness function which was linearly combined of sinusoidal functions with frequencies exponential to a positive integer *m*, a base-*m* encoding could achieve higher AEP than encodings with bases other than *m*. The simulation results show that, the optimization performance and the rise time of the average fitness of the population under a base-*m* encoding are significantly better than those of the other encodings.
%U http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2017.07.1972