改进的蚁群遗传算法求解旅行商问题  

Improved Ant Colony- Genetic Algorithm for Solving TSP

作　　者：于莹莹[1] 陈燕[1] 李桃迎[1] 

机构地区：[1]大连海事大学交通运输管理学院,辽宁大连116026

出　　处：《计算机仿真》2013年第11期317-320,共4页Computer Simulation

基　　金：国家自然科学基金(71271034);辽宁省教育厅科学研究一般项目(L2012173)

摘　　要：在改进蚁群算法优化问题的研究中,针对遗传算法收敛速度过慢的问题,将蚁群算法与遗传算法相结合,首先利用信息素的蚁群算法的快速收敛特性,得到一次寻优结果作为遗传算法的初始种群,同时对传统遗传算法的基本遗传算子做出改进,结合形成一种新的算法模型,应用于求解旅行商问题。对三种模型分别设计程序实现仿真,采用两组实验数据,对三种算法求解旅行商问题的结果进行模拟与对比分析。实验结果表明改进的蚁群遗传结合算法可以有效地解决旅行商问题,在求解效率和求解质量上都取得很好的效果。As the convergence speed of Genetic Algorithm is slow, a new combination method based on Ant Colo- ny Algorithm and Genetic Algorithm for solving TSP was proposed. The new method took the result of Ant Colony Al- gorithm based on pheromone as the initial population of Genetic Algorithm, and makes a few improvements about the Genetic Algorithm. Finally, to illustrate it more clearly, a program based on these three algorithms or solving TSP was implemented. Through the experiments and the contrast of the results, it is proved that the new combination algorithm can effectively improve the accuracy and the quality of the results, and speed up the convergence and computation distinctly.

关 键 词：蚁群算法 遗传算法 组合算法 旅行商问题 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TP18[自动化与计算机技术—计算机科学与技术]