Korzeń Mariusz, Gisterek Igor
Department of Civil Engineering, Wrocław University of Science and Technology (Politechnika Wrocławska), Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland.
Sensors (Basel). 2024 Sep 26;24(19):6226. doi: 10.3390/s24196226.
Nature-inspired algorithms allow us to solve many problems related to the search for optimal solutions. One such issue is the problem of searching for optimal routes. In this paper, ant colony optimization is used to search for optimal tram routes. Ant colony optimization is a method inspired by the behavior of ants in nature, which as a group are able to successfully find optimal routes from the nest to food. The aim of this paper is to present a practical application of the algorithm as a tool for public transport network planning. In urban public transport, travel time is crucial. It is a major factor in passengers' choice of transport mode. Therefore, in this paper, the objective function determining the operation of the algorithm is driving time. Scheduled time, real time and theoretical time are analyzed and compared. The routes are then compared with each other in order to select the optimal solution. A case study involving one of the largest tramway networks in Poland demonstrates the effectiveness of the nature-inspired algorithm. The obtained results allow route optimization by selecting the route with the shortest travel time. Thus, the development of the entire network is also possible. In addition, due to its versatility, the method can be applied to various modes of transport.
受自然启发的算法使我们能够解决许多与寻找最优解相关的问题。其中一个问题就是寻找最优路线的问题。在本文中，蚁群优化算法被用于搜索最优电车路线。蚁群优化算法是一种受自然界蚂蚁行为启发的方法，蚂蚁群体能够成功地找到从巢穴到食物的最优路线。本文的目的是展示该算法作为公共交通网络规划工具的实际应用。在城市公共交通中，出行时间至关重要。它是乘客选择交通方式的一个主要因素。因此，在本文中，决定算法运行的目标函数是行驶时间。对计划时间、实时时间和理论时间进行了分析和比较。然后将各路线相互比较以选择最优解。一个涉及波兰最大的有轨电车网络之一的案例研究证明了这种受自然启发的算法的有效性。所获得的结果允许通过选择行驶时间最短的路线来优化路线。因此，整个网络的发展也是可能的。此外，由于其通用性，该方法可应用于各种交通方式。
