Rail Transportation Network Design using Greedy Algorithm Based on Maximum Impact on Travel Time - Case Study: Railway of Iran

The railway network design problem deals with how to allocate a limited budget for the development of the railway network infrastructure. Among the objectives used in this problem, we can mention the minimization of the total travel time in the network, the minimization of the development costs, or the maximization of the income. Considering that the two groups of decision-makers are influential in this problem, the general form of the network design problem will be a Bi-level problem that belongs to the category of NP-Hard problems, which cannot be solved using precise optimization methods in even small scales. In this article, an innovative approximate greedy algorithm is presented to solve the problem of rail network design. In this algorithm, the focus is on developing blocks of the rail network that have the greatest effect in reducing the average travel time in the network. The process of adding blocks in the network continues until the entire level of incoming demand can be transferred from the network. This algorithm was implemented with Java language and railway of Iran has been selected as a case study. The results show that with the development of the network up to the demand of 57 million tons, the average travel time will reach its lowest value; and for the higher demand values, the average travel time will increase.