Prioritization of transfer centers using GIS and fuzzy Dombi Bonferroni weighted Assessment (DOBAS) model

In pursuit of a sustainable and ecologically conscious future, as enhancing railway infrastructure became specifically important, strategic positioning of railway stations is a growing concern for regulatory authorities. Strategic positioning is a complex problem and requires comprehensive approach....

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Veröffentlicht in:Expert systems with applications 2024-03, Vol.238, p.121827, Article 121827
Hauptverfasser: Önden, İsmail, Pamucar, Dragan, Deveci, Muhammet, As, Yakup, Birol, Batın, Şüheda Yıldız, Feride
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Sprache:eng
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Zusammenfassung:In pursuit of a sustainable and ecologically conscious future, as enhancing railway infrastructure became specifically important, strategic positioning of railway stations is a growing concern for regulatory authorities. Strategic positioning is a complex problem and requires comprehensive approach. Multifaceted parameters such as proximity to production centers, integration with port facilities and transport networks, transportation infrastructure quality, and railway capacity should be taken into account. This study aims to analyze the decision-making process in strategic positioning of railway stations. To this end, the problem is formalized in multi-criteria decision-making (MCDM) context. Spatial data, statistical insights, and expert opions are used to form evaluation criateria. Then, a novel model, Fuzzy Dombi Bonferroni Weighted Assessment (DOBAS) is introduced so that Geographic Information System (GIS) outputs can be considered together with capacity calculations. After the challenges of the model are solved and sensitivity analysis are done, it is demonstarted in a case of one of the most logistically dense regions of Turkey to show that the model provides an efficient way of prioritizing a freight corridor. Outcomes show that geographical locations, easiness of integration to the existing transportation system and complemantary sectors in the neighborhood are effective. Results are extended and discussed to reach policy implications for regulatory authorities.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2023.121827