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一种基于改进全局信息素更新效率的蚁群算法及仿真

         

摘要

针对目前蚁群算法在搜索过程花费时间长且易出现局部最优化等现象,提出一种基于改进全局信息素更新效率的蚁群算法。通过在蚁群算法中引入“精英策略”,让算法的搜索具有一定的方向性,并且在此基础上对信息素初始值的定义与对算法中的挥发因子ρ的取值进行改进,从而缩短算法的搜索时间。通过验证,改进后的算法相比一般的蚁群算法具有更好的搜索效率与较高的精确性,更适用于比较大型的TSP问题,在路径搜索领域具有较好的发展前景。%On account of the phenomena that current ant colony algorithm takes a long time in the search process and is prone to local optimisation,we present an ant colony algorithm which is based on improving the efficiency of global pheromone update.Through introducing the "elite strategy"to ant colony algorithm,the search in the algorithm is enabled to have certain directivity,and on this basis the definition of the initial value of pheromone and the valuing of the volatile factor ρin the algorithm are both improved,thereby the search time of the algorithm is shortened as well;Through the verification ,the improved algorithm proposed in the paper has better search efficiency and higher accuracy in comparison with the general ant colony algorithms,it is more suitable for the plus large-scale TSP problems,and has good development prospects in the field of multi-path search.

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