论文部分内容阅读
针对蚁群算法存在的不足,提出一种改进蚁群优化算法——参数模糊自适应窗口蚁群优化算法.首先利用模糊控制优化α,β和ρ参数,同时为蚂蚁建立动态搜索窗口,在为每只蚂蚁建立近邻城市表时加入混沌信息,并据此进行初始信息素分布.另外,引入了城市节点活跃度的概念,并将其作为未来信息,用以指导蚂蚁进行解的构造和信息素更新.仿真结果表明,即使在复杂的环境下,所提出的算法仍能快速规划出安全的最优路径.
Aiming at the deficiency of ant colony algorithm, this paper proposes an improved ant colony optimization algorithm - parameter fuzzy adaptive window ant colony optimization algorithm.Firstly, α, β and ρ parameters are optimized by fuzzy control, and a dynamic search window is established for ant, When each ant creates the neighbor city list, chaos information is added, and then the initial pheromone distribution is derived.In addition, the concept of city node activity degree is introduced and used as future information to guide the ant’s construction and pheromone The simulation results show that the proposed algorithm can quickly plan the optimal path of security even in complex environment.