摘要
针对基本遗传算法收敛速度慢,易早熟等问题,提出一种改进的遗传算法。新算法利用贪婪思想产生初始种群来加快寻优速度,用贪婪思想来引导交叉操作,在交叉操作之前,把当前较差的一半种群替换成随机种群,最后用改进的变异算子和进化逆转操作进行寻优,利用新的遗传算法求解基本的旅行商问题。仿真结果表明,改进的遗传算法具有全局搜索能力强、收敛速度快的特点,优化质量和寻优效率都较好。
Aiming at the problem of slow convergence and easy premature convergence, an improved genetic algorithm is proposed. New algorithm uses greedy idea to generate the initial population for speeding up the searching speed and greedy idea to guide the crossover operation, before the crossover operation, selects the random population to replace the half of the poor population, finally with the help of the improved mutation operator and evolutionary reversal operation to realize optimization, constructs a new genetic algorithm for solving the traveling salesman problem. The simulation results show that the improved genetic algorithm has the characteristics of strong global search ability and fast convergence speed.
作者
陈林
潘大志
CHEN Lin PAN Dazhi(College of Mathematics and Information, China West Normal University, Nanchong Sichuan 637009, Chin)
出处
《智能计算机与应用》
2016年第5期17-19,23,共4页
Intelligent Computer and Applications
基金
四川省教育厅自然科学基金(14ZA0127)
西华师范大学博士启动基金(12B022)
校级创新团队(CXTD2015-4)
关键词
遗传算法
贪婪思想
进化逆转
旅行商问题
genetic algorithm
greedy idea
evolutionary reversal
traveling salesman problem
