Freight transport is a key enabler for the growth of the national industry and the opportunity to leverage Iran’s geographical position for freight transit. The main challenge facing Iran railways is prioritizing commodity groups. Given the dynamic conditions of rail transport in Iran, the use of dynamic MCDM models is inevitable. This study aims to develop a model that prioritizes alternatives based on the desirability they create over a finite future horizon. In all previous studies on dynamic multi-criteria decision-making, the behavior of alternatives with respect to criteria has been extracted periodically. The challenging subject for the implementation of these models is the correct choice of period length in which the information is extracted. Otherwise, this may be associated with the loss of information between periods. Therefore, we decided to develop models, which consider the behavioral changes of alternatives with respect to criteria, continuously. The models contain nine commodity groups as alternatives and "tonnage", "ton-kilometer" and "average revenue per ton-kilometer" as criteria. The findings derived from implementing the model reveal that minerals are poised to attain the highest rank in future. Furthermore, the subsequent ranks are anticipated to be occupied by Petroleum Products and industrial materials.
Nejatnia, M. , Makui, A. and Jabbarzadeh, A. (2023). Developing a continuous dynamic multi criteria decision making model for ranking commodity groups in Iran railways. Scientia Iranica, (), -. doi: 10.24200/sci.2023.62009.7597
MLA
Nejatnia, M. , , Makui, A. , and Jabbarzadeh, A. . "Developing a continuous dynamic multi criteria decision making model for ranking commodity groups in Iran railways", Scientia Iranica, , , 2023, -. doi: 10.24200/sci.2023.62009.7597
HARVARD
Nejatnia, M., Makui, A., Jabbarzadeh, A. (2023). 'Developing a continuous dynamic multi criteria decision making model for ranking commodity groups in Iran railways', Scientia Iranica, (), pp. -. doi: 10.24200/sci.2023.62009.7597
CHICAGO
M. Nejatnia , A. Makui and A. Jabbarzadeh, "Developing a continuous dynamic multi criteria decision making model for ranking commodity groups in Iran railways," Scientia Iranica, (2023): -, doi: 10.24200/sci.2023.62009.7597
VANCOUVER
Nejatnia, M., Makui, A., Jabbarzadeh, A. Developing a continuous dynamic multi criteria decision making model for ranking commodity groups in Iran railways. Scientia Iranica, 2023; (): -. doi: 10.24200/sci.2023.62009.7597