Evaluation of the TCIS Influence on the capacity utilization using the TOPSIS method: Case studies of Serbian and Austrian railways

  • Evelin Krmac University of Ljubljana, Faculty of Maritime Studies and Transport
  • Boban Djordjević University of Ljubljana, Faculty of Maritime Studies and Transport
Keywords: Evaluation, Train Control Information System, Railway, Capacity, Multicriteria Decision Making


Increasing of train traffic on railway infrastructure implies the use of enlarged railway network capacity and the corresponding increase in intelligence - i.e. “intelligentization” - of railway industries. As the Train Control Information System (TCIS) results as one of the most important railway systems with a significant impact on overall railway performance is very important to be able to evaluate its efficiency and influence on railway infrastructure capacity (RIC). In this paper, the model for evaluation of the influence of TCIS on capacity utilization, based on the TOPSIS method is proposed as an alternative to DEA based models. Indeed, the main drawback of DEA based models is that DEA evaluates the alternatives from only one point of view and classifies them as efficient or inefficient, while TOPSIS allows the benchmarking of the alternatives by detecting the best practices based on the ranking of alternatives. For the purposes of this paper, the TOPSIS based evaluation where years represent alternatives were tested through case studies of Serbian and Austrian railways for the period from 2006 to 2015. Based on the obtained results it can be pointed out that TOPSIS method can be applied for the evaluation and comparison of the influence of different TCIS on RC utilization.


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How to Cite
Krmac, E., & Djordjević, B. (2019). Evaluation of the TCIS Influence on the capacity utilization using the TOPSIS method: Case studies of Serbian and Austrian railways. Operational Research in Engineering Sciences: Theory and Applications, 2(1), 27-36. Retrieved from http://www.oresta.org/index.php/oresta/article/view/16