A New Genetic Algorithm Based on Negative Selection

Genetic algorithm offers the common frame of resolving optimization problem by imitating biological evolution based on natural selection. However it has some drawbacks such as slow convergence and being premature. In genetic algorithm, individual generated by genetic operation is a bit random and even sometimes more inferior than its parents. So a new operator - negative selection that can filtrate bad-quality individual is introduced to genetic algorithm to speed up its speed of convergence and improve its global searching ability. With this new operator, a new optimization algorithm based genetic algorithm and negative selection is proposed. Furthermore this paper shows its ability to solve the function optimization problem