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Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System

机译:Bee启发的铁路系统有效和高效路线规划的新型优化算法和数学模型

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摘要

Railway and metro transport systems (RS) are becoming one of the popular choices of transportation among people, especially those who live in urban cities. Urbanization and increasing population due to rapid development of economy in many cities are leading to a bigger demand for urban rail transit. Despite being a popular variant of Traveling Salesman Problem (TSP), it appears that the universal formula or techniques to solve the problem are yet to be found. This paper aims to develop an optimization algorithm for optimum route selection to multiple destinations in RS before returning to the starting point. Bee foraging behaviour is examined to generate a reliable algorithm in railway TSP. The algorithm is then verified by comparing the results with the exact solutions in 10 test cases, and a numerical case study is designed to demonstrate the application with large size sample. It is tested to be efficient and effective in railway route planning as the tour can be completed within a certain period of time by using minimal resources. The findings further support the reliability of the algorithm and capability to solve the problems with different complexity. This algorithm can be used as a method to assist business practitioners making better decision in route planning.
机译:铁路和地铁运输系统(RS)成为人们特别是居住在城市人群中的一种普遍的交通选择。由于许多城市经济的快速发展,城市化和人口增加正在导致对城市轨道交通的更大需求。尽管它是旅行商问题(TSP)的流行变体,但似乎尚未找到解决该问题的通用公式或技术。本文旨在开发一种优化算法,以在返回起点之前针对RS中的多个目的地进行最佳路线选择。检查了蜜蜂的觅食行为,以在铁路TSP中生成可靠的算法。然后通过将结果与10个测试用例中的精确解进行比较来验证该算法,并设计了一个数字案例研究来说明大样本量的应用。经测试,此方法在铁路路线规划中非常有效,因为只需最少的资源即可在一定时间内完成游览。这些发现进一步支持了算法的可靠性以及解决不同复杂性问题的能力。该算法可用作协助业务从业人员在路线规划中做出更好决策的方法。

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