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首页> 外文期刊>The international arab journal of information technology >Using the Ant Colony Algorithm for Real-Time Automatic Route of School Buses
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Using the Ant Colony Algorithm for Real-Time Automatic Route of School Buses

机译:使用蚁群算法实时校车自动路由

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Transportation and distribution systems are improving with an increasing pace with the help of current technological facilities and additionally, the complexity of those systems are increasing. Vehicle Routing Problems (VRPs) are difficult to solve with conventional techniques. Improving routes used in distribution systems provides significant savings in terms of time and costs. In this paper, current routes in school buses, which is a sub-branch of vehicle routing problems, are optimized using the Ant Colony Optimization (ACO), which is a heuristic artificial intelligence algorithm. Developed software is used for recommending the most suitable and the shortest route illustrated on a map by taking the instantaneous student wait locations online. Results of this study suggest that the current routes can be improved by using the ACO.
机译:在现有技术设施的帮助下,运输和分配系统正在以越来越快的速度发展,此外,这些系统的复杂性也在增加。车辆路线问题(VRP)很难用常规技术解决。改进配电系统中使用的路线可以节省大量时间和成本。在本文中,校车中的当前路线是车辆路线问题的子分支,它是使用启发式人工智能算法蚁群优化(ACO)进行优化的。开发的软件用于通过在线即时学生等待位置来推荐地图上所示的最合适和最短路线。这项研究的结果表明,使用ACO可以改善当前路线。

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