基于信息素扩散的优化蚁群算法的研究  

The Ant Colony Algorithm Optimization on Pheromone Diffusion

作　　者：王兰春[1] 

机构地区：[1]忻州师范学院,山西忻州034000

出　　处：《计算机光盘软件与应用》2010年第14期12-13,共2页Computer CD Software and Application

摘　　要：在蚁群算法实验性分析的基础上，对算法模型改进和信息素更新机制方面，首次引入了信息素扩散的概念，在信息素更新的时候更好地考虑了先前经过的节点，以尽力避免不必要的无用搜索，同时基于信息素扩散的蚁群算法具有不断获得新的最优解的能力，使得改进蚁群算法在不断的迭代过程后，可获得全局最优解，而不易陷入局部最优解。在解决实际旅行商问题时，首先对所有节点的坐标预处理，然后采取信息素扩散机制和蚂蚁泛滥技术来对蚁群算法进行改进，力求在相同的迭代次数内可以寻找到更短及代价更小的路径。最后，通过在VC＋＋环境下实现改进蚁群算法程序，验证了改进后的蚁群算法的可行性以及改进后的蚁群算法求解的高效性。The experimental analysis of ant colony algorithm based on the improvement algorithm model and the updated pheromone mechanism,first introduced the concept of pheromone diffusion,in better updated pheromone when the node was previously considered,useless to try to avoid the unnecessary search,while pheromone-based ant colony algorithm has been spread of the optimal solution to gain new capabilities,making the improved ant colony algorithm in continuous iterative process,get the global optimal solution,not easily fall into local optimal solution.In solving the traveling salesman problem,first the coordinates of all nodes pretreatment,and then take the ant pheromone diffusion mechanism and the proliferation of technology to improve the ant colony algorithm,and strive in the same number of iterations can find the cost of a shorter and smaller paths.Finally,in the VC＋＋ environment to achieve improved ant colony algorithm to verify that the improved ant colony algorithm feasible and improved ant colony algorithm is efficient.

关 键 词：蚁群算法 信息素扩散 蚂蚁泛滥技术 信息素 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]