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The implementation of genetic algorithm based on optimizing search space partition

The bottlenecks which restrict genetic algorithm are premature convergence and easy to fall into local, and the reasons of premature convergence mainly include population size, genetic manipulation, initial population distribution and other factors. Therefore, the optimizing search space algorithm by using taboo domain and effective domain partition can effectively reduce the search space and avoid premature algorithm. This paper studies and discusses the code, operator design and the selection and realization of control parameters of the implementation of stable genetic algorithm of elitist genetic sense units through optimizing search space partition, and the experiments show that the global search and local search ability of algorithm are greatly improved compared with other genetic algorithms, and the average convergence velocity and efficiency of the convergence to the optimum solution is superior to other genetic algorithms.