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首页> 外文期刊>International Journal of Bio-Inspired Computation >Using the metaheuristic methods for real-time optimisation of dynamic school bus routing problem and an application
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Using the metaheuristic methods for real-time optimisation of dynamic school bus routing problem and an application

机译:使用Metaheuristic方法进行动态校车路由问题的实时优化和应用

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摘要

The vehicle routing problem (VRP) is an optimisation issue that has been studied for more than 50 years with its numerous subfields. The optimisation of VRP over distribution and transportation systems leads to significant gains in cost and time. There are many metaheuristic methods developed for the solution of the problem; and it was observed that metaheuristic methods prove to produce more successful results compared to common heuristic methods. In this study, a mobile-supported visual application was developed using ant colony optimisation (ACO) and genetic algorithm (GA), which are among the metaheuristic methods for the dynamic school bus routing problem (DSBRP), one of the sub-problems of VRP. The ACO and GA methods were utilised via the application for bus routes of a school located in the province of Ankara and the performance of these methods were compared through the obtained results. It was observed that time and distance values of the routes of current school bus routes may be improved by these two methods.
机译:车辆路由问题(VRP)是一项优化问题,已通过其众多子场进行了50多年。 VRP过度分配和运输系统的优化导致成本和时间的显着增益。有许多用于解决问题的核心型方法;并且观察到,与常见的启发式方法相比,成群质方法证明了产生更成功的结果。在本研究中,使用蚁群优化(ACO)和遗传算法(GA)开发了一种移动支持的可视应用,这些应用是动态校车路由问题(DSBRP)的成群质方法中的一个子问题之一VRP。通过申请ANKARA省内的学校的公共汽车路线使用ACO和GA方法,并通过所获得的结果进行比较这些方法的性能。观察到,目前校车路线的时间和距离值可以通过这两种方法得到改善。

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