摘要
传统的优化算法对于复杂的函数往往不能取得满意的结果 ,而遗传算法作为一种全局搜索策略 ,较传统的优化算法更加优越。对遗传算法的杂交、变异算子进行了改进 ,并加入单纯形算子。通过对函数求最优值的测试 ,证明这种改进使遗传算法的收敛速度加快。
Satisfying results can not be obtained when traditional algorithms are used to solve complex function optimization problems. But as a global searching strategy, the Genetic Algorithm does better than the traditional algorithms. The crossover operator and mutation operator are improved, which are used in a simple genetic algorithm, and a simplex operator is added in this improved genetic algorithm. Results of an experiment show that this improved algorithm not only converges quickly, but also enhances the quality of the results.
出处
《武汉理工大学学报（信息与管理工程版）》
CAS
2002年第3期15-17,共3页
Journal of Wuhan University of Technology：Information & Management Engineering
关键词
遗传算法
函数优化
单纯形
genetic algorithm
function optimization
simplex
