个体变异蚁群算法在TSP问题中的应用研究

在蚁群算法中引入个体变异机制,使蚁群中蚂蚁个体的参数产生差异,从而调整概率函数中信息素因子的强度以及距离因子在概率中的作用,使蚂蚁在选路时具有多样性.与传统蚁群算法的对比实验表明该算法加快了收敛速度,改善了求解性能,有效避免了早熟收敛.

Abstract：

Ant colony algorithm has many disadvantages, such as long searching time, easy to fall into the local optimal solution and so on. This paper bring a individual mutation strategy in ACA, which makes the parameters of individual in the ant colony cause to change, enables the strategy of ants route selection to possess variety by coordinating the intensity of the pheromone gent and the effect of the distance gene in the probability function. The experimental results show that the improved algorithm has great effectiveness and efficiency than the Ant Colony algorithm and avoid stagnation efficiently.

Research of the Application of TSP Problems Based on Individual Mutation Ant Colony Optimization Algorithm