可控搜索偏向的二元蚁群算法  

Binary ant colony algorithm with controllable search bias

作　　者：胡钢[1] 熊伟清[1] 张翔[1] 袁军良[1] 

机构地区：[1]宁波大学电子商务研究所,浙江宁波315211

出　　处：《控制理论与应用》2011年第8期1071-1080,共10页Control Theory & Applications

基　　金：浙江省自然科学基金资助项目(Y1080364);宁波市自然科学基金资助项目(Y1100052)

摘　　要：蚁群算法按照信息素轨迹产生的偏向对解空间进行搜索.当前改进蚁群算法性能的主要方法是提高种群的多样性,少有对搜索偏向进行控制.本文以可控搜索偏向作为研究的出发点,通过对至今最优信息素更新方式的分析,得出了从任意代到算法收敛没有发现较优解的概率下限.并以此为基础,把访问量与蚂蚁数量的关系作为控制偏向的依据,在兼顾提高种群多样性的前提下,设计了可控搜索偏向的二元蚁群算法.通过多个函数的测试以及0-1多背包问题的应用,其实验结果表明该算法有较好的搜索能力以及较快的收敛速度.Ant colony algorithm explores the solution space according to the bias produced by pheromone trail. However, most of the existing improvements concentrate in raising the population diversity, instead of controlling the search bias. On the basis of the controllable search bias and by the update pattern of the current pheromone, we determine for any given iteration the lower bound of the probability of no further improvement in solution up to the convergence. Using the relation between the number of visitors and the ant population, and considering the population diversity, we develop a binary ant colony algorithm with controllable search bias. In the test of function optimization and the application to the 0-1 multiple knapsack problem, the algorithm exhibits a good search ability and a high convergence speed.

关 键 词：蚁群算法 二元蚁群算法 信息素更新方式 可控搜索 函数优化 0-1多背包问题 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]