改进状态转移策略的蚁群算法求解TSP问题

Ant Colony Algorithm for Improving State Transfer Strategy to Solve TSP Problem

针对蚁群算法在求解TSP问题中易出现算法易早熟难收敛的问题,基于历史搜索信息提出了一种改进状态转移策略的蚁群算法,并引入自适应信息素更新机制引导信息素的更新。实验表明,改进的蚁群算法较传统蚁群算法改善了在求解TSP问题上易早熟难收敛的问题,求解效果和求解稳定性上提升显著。

Aiming at the problem of ant colony algorithm in solving TSP problem,the algorithm is easy to premature and difficult to converge.Based on historical search information,an ant colony algorithm with improved state transition strategy is proposed,and an adaptive pheromone update mechanism is introduced to guide the update of pheromone.Experiments show that the improved ant colony algorithm improves the problem of premature convergence and difficulty in solving the TSP problem compared with the traditional ant colony algorithm.The solution effect and stability of the solution are significantly improved.