Ant colony optimisation for finding the optimal railroad path

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.