Evaluation of the railway management model by using a new integrated model DELPHI-SWARA-MABAC

Decision Making: Applications in Management and Engineering

Slavko Vesković¹  Sanjin Milinković¹  Marko Vasiljević²  Željko Stević³  Gordan Stojić⁴ 

[1] University of Belgrade, Faculty of Transport and Traffic Engineering, Belgrade, Serbia;University of East Sarajevo, Faculty of Transport and Traffic Engineering Doboj, Bosnia and Herzegovina;University of East Sarajevo, Faculty of Transport and Traffic Engineering, Doboj, Bosnia and Herzegovina;University of Novi Sad, Faculty of Technical Science, Novi Sad, Serbia;

关键词: Railways, Transport Policy, Delphi, SWARA, MABAC;   

DOI  :  

来源: DOAJ

【 摘 要 】

The functioning of each traffic system depends to a great extent on the way the rail transport system operates. Taking into account the aspect of market turbulence and the dependence on adequate delivery when it comes to freight transport and traffic in accordance with a yearly Timetable in passenger traffic, transport policies are changing with time. Therefore, this document is considering the railway management models on the territory of Bosnia and Herzegovina. For the purpose of evaluating these models, a new hybrid model has been applied, i.e. the model which includes a combination of the Delphi, SWARA (Step-Wise Weight Assessment Ratio Analysis) and MABAC (Multi-Attributive Border Approximation Area Comparison) methods. In the first phase of the study, the criteria ranking was determined based on 16 expert grades used in the Delphi Method. After that, a total of 14 decision-makers determined the mutual criteria impact, which is a prerequisite for the application of the SWARA Method used to determine the relative weight values of the criteria. The third phase involves the application of the MABAC Method for evaluating and determining the most suitable variant. In addition, a sensitivity analysis involving the application of the ARAS, WASPAS, SAW and EDAS methods has been performed, thus verifying the previously obtained variant ranking.

【 授权许可】

Unknown