Improved exponentiation scale transformation in application of genetic algorithm
Yang Shuiqin · Computer Engineering and Applications Journal · 2014
It is the main factors for fitness functions to guide the search of the genetic algorithm optimization process.The exponential fitness functions are improved by exponentiation scale transformation. They are used to evaluate several common fitness functions to keep their diversity of population and convergence of the algorithms. The optimal computation is compared for the usual and the improved fitness functions under the same conditions of genetic manipulation and their parameters in using three typical test functions. Numerical results show that it is significant for the new fitness functions of a power optimal algorithm to improve the overall performance including the accuracy, convergence speed, and convergence stability of the ameliorated genetic algorithms.