基于细粒度模型的并行蚁群优化算法

蚁群优化算法的研究和应用已取得了不少重要成果，然而在大规模优化应用中还存在搜索时间长的问题，为此研究了一种基于细粒度模型的并行蚁群算法。实验结果表明，该算法与最新的改进算法相比，搜索速度提高数十倍至数百倍以上。

Ant Colony Optimization Parallel Algorithm Based on Fine grained Model

Although a good many important results have been achieved about the research of Ant Colony Optimization (ACO) algorithm and its application,the time required to find good optimal solution is unbearable for large scale optimization problems.Therefore,ant colony optimization parallel algorithm base on fine-grained model is proposed to improve its performance in this paper.The results of experiment show that the algorithm described in this paper make the searching speed hundreds of times faster than the latest improved one.