The Application of Improved Genetic Algorithm in Optimization of Function
This paper points out defects of the traditional genetic algorithm (TGA), and has made improvement in it. An optimization strategy of combination is described. The improved genetic algorithm (IGA) is used to search the better answer in the whole feasible domain, and TGA is used to find the best answer in the local domain. The example shows the rationality and efficiency of this algorithm. This algorithm improves population diversity in the process of evolution, adapting bigger probability of crossover and mutation.
traditional genetic algorithm optimization improved genetic algorithm crossover and mutation
TAN Ran GUO Shaoyong
School of Computer Science and Technology Wuhan University of Technology Wuhan, Hubei 430063.P.R.China
国际会议
大连
英文
1-4
2008-10-12（万方平台首次上网日期，不代表论文的发表时间）