多蚁群双信息素疏散路径规划算法

Evacuation Path Planning Algorithm Based on Multi-ant-colony Dual-pheromone

针对综合交通枢纽的常规旅客疏散问题,以最小化清空时间、最小化累计拥堵系数和最小化人均疏散时间为疏散目标,提出多蚁群双信息素算法。根据乘车意向将疏散人员划分为多个种群,引入种群信息和部落信息素,利用种群信息素的正反馈作用实现同一种群人员的路径寻优,利用部落信息素的负反馈作用实现路径的均衡负载。与ACO和HMERP-ACO算法进行对比,结果表明,提出的算法可以提供更优的疏散路径规划方案。

In view of conventional passenger evacuation at comprehensive transportation hubs,a multi-ant-colony dual-pheromone algorithm was proposed to minimize clearance time,cumulative congestion coefficient and per-capita evacuation time.According to their riding intention,evacuators were divided into different populations.Moreover,population pheromone and tribe pheromone were introduced.Path optimization was realized for passengers of the same population by using the positive feedback action of the population pheromone,while the negative feedback of the tribe pheromone was used to balance path load.A comparison was made with ACO and HMERP-ACO.Experimental results showed that the proposed algorithm could provide a better scheme for planning evacuation paths.