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Ant colony optimisation for finding the optimal railroad path

机译:蚁群优化以找到最佳铁路路径

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摘要

Engineers have applied mathematical models to find the optimal railway path in order to minimise the total cost subject to the railway limitations. There are two main issues for this problem. First, this approach results in a complex formulation for real-life applications, mainly because there are a huge number of variables and constraints. Second, to compute the total cost, different types of data are required, such as topography, right-of-way unit cost, forbidden zones and geology. Because various administrations are often responsible for preparing these data with their own standards, there is much inconsistency in the data. This paper deals with the first issue by proposing a high-performance optimisation technique that simulates the behaviour of ants to obtain a good optimum. To show the effectiveness of this algorithm in finding a solution, a comparison with common algorithms is presented. In addition, a geographical information system database is used to obtain all the necessary data to estimate the total cost for each rail path. Finally, the proposed algorithm is tested to find the optimal path in a hypothetical area and the result of the proposed algorithm for finding the path is validated.
机译:工程师已经应用数学模型来找到最佳的铁路路径,以便在铁路局限的情况下将总成本降至最低。此问题有两个主要问题。首先,这种方法导致了针对现实应用的复杂表述,主要是因为存在大量的变量和约束。其次,要计算总成本,需要使用不同类型的数据,例如地形,通行权单位成本,禁区和地质。由于各个主管部门通常负责按照自己的标准来准备这些数据,因此数据存在很多不一致之处。本文通过提出一种高性能优化技术来处理第一个问题,该技术可以模拟蚂蚁的行为以获得良好的最优性能。为了显示该算法在寻找解决方案中的有效性,提出了与常见算法的比较。此外,地理信息系统数据库用于获取所有必要数据,以估算每条铁路路径的总成本。最后,对提出的算法进行了测试,以在假设的区域内找到最佳路径,并验证了提出的算法的结果。

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