Developing a framework for prioritizing railway infrastructure projects; using a hybrid Value Engineering-ANP technique

A large portion of the budget of many countries in the world is spent on the transportation projects. Often these projects are capital-intensive in the all of transportation systems, and for this reason, any savings -even small saving- in these projects, could lead to considerable economic benefits. The value engineering is one of the powerful management and cost saving techniques that is capable of significant decreasing in construction cost and time, as well as increasing project performance and value.
In many cases, due to budget limitation, concurrent implementation of multiple projects in the transportation sector is not possible and it is essential that the approved projects prioritized and implemented based on specified criteria. The value engineering focuses on the criteria which could lead to the significant decreasing in the project implementation cost and time, and elimination of unnecessary activities. This research is based on railway transportation expert comments for developing eleven appropriate criteria using value engineering concept for evaluation and prioritizing five projects of the new rail lines construction by applying an ANP model. Based on the results, implementing the “bam-jiroft” project has the highest implementation priority and also the “implementation cost” criterion has the greatest weight compared to other used criteria. In addition based on the results of this study, a framework is proposed for review in the budget allocation management according to the weight of each project which it can be used to reform the current system of budget allocation. In the following, in order to analyze the results, the obtained results of the ANP are confirmed by using four other decision-making models. Also the sensitivity analysis results show that the proposed prioritization model has the highest sensitivity to the “reducing the number of road accidents” criterion and the lowest sensitivity to the “operating cost” criterion.