基于病毒侵染和逆转操作的改进遗传算法  

The improved genetic algorithm based on virus invading and reverse operation

作　　者：刘艳琪[1] 刘一杰 Liu Yanqi;Liu Yijie(School of Mathematics and Physics,University of South China,Hengyang 421001,China)

机构地区：[1]南华大学数理学院,湖南衡阳421001

出　　处：《湖南文理学院学报（自然科学版）》2022年第3期23-29,共7页Journal of Hunan University of Arts and Science(Science and Technology)

基　　金：教育部大学生创新创业训练计划(S201910555115)。

摘　　要：针对传统遗传算法解决TSP问题,提出了加入病毒种群来感染初始种群,并将种群分为父代和子代种群实现逆转操作的改进遗传算法。加入病毒种群来感染初始种群加快了遗传算法的收敛速度,通过逆转操作使算法更容易跳过局部最优解,避免遗传算法在大规模问题中易陷入局部最优解的问题。以两组实验来对比改进算法性能与传统算法性能的差别,结果表明改进算法的执行效率和执行结果明显优于传统遗传算法。最后利用改进后的遗传算法遍历中国34座省会城市的最优路线,验证了该算法的准确性和优越性。To give a bullet to the questions of TSP,an improved genetic algorithm is rendered,which infects the initial population by adding virus population,and classifies the population into parent and offspring populations to realize the reverse operation.As adding a virus population to infect the initial population speeds up the convergence of genetic algorithm,it is easier for the algorithm to skip the locally optimal solution through reverse operation.This helps to avoid the hiccup that genetic algorithm is vulnerable to falling into the locally optimal solution in a large swath of problems.Two groups of experiments are given to investigate the performance of the improved algorithm comparing with a traditional one.It is evident that the improved algorithm is better than the traditionally genetic one in execution efficiency and results.Finally,the improved genetic algorithm is used to traverse the optimal routes of 34 provincial capitals in China,verifying the accuracy and superiority of this algorithm.

关 键 词：TSP问题 遗传算法 优化 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]