Research on genetic algorithm based on the crest value of binary function

摘要

Genetic algorithm is a computational model to simulate the biological evolution process of genetic mechanism and natural selection. At present, genetic algorithm has been widely used in optimization & combination, signal processing, self-adaption control, machine learning and artificial intelligence .Meanwhile, it has got a lot of attention at home and abroad. In genetic algorithm, function optimization is a typical application. The purpose of this paper is to use the genetic algorithm to simulate the optimized calculation process of binary function’s crest value, through the specific examples of binary function, and finally get the optimal solution of binary function’s maximum value. The genetic algorithm mainly includes individual encoding, population initialization, fitness calculation, selection operation, crossover operation and mutation operation, and the selection operation, crossover operation and mutation operation are the three main operators of genetic algorithm. In the genetic algorithm process, there should be iterated several times, in each iteration, to select, crossover and mutate [1] , eliminating the individuals with lower fitness , looking for individuals with better fitness, and eventually find the individual with highest fitness , for solving the maximum value of binary function.