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Article type: Research Article
Authors: Oztaysi, Basar* | Cevik Onar, Sezi | Kahraman, Cengiz
Affiliations: Istanbul Technical University, Department of Industrial Engineering, Macka Istanbul, Turkey
Correspondence: [*] Corresponding author. Basar Oztaysi, Istanbul Technical University, Department of Industrial Engineering, 34367 Macka Istanbul, Turkey. Tel.: +90 212 2931300/2669; Fax: +90 212 24072 60; E-mail: oztaysib@itu.edu.tr.
Abstract: Urban transformation projects are prepared with the purpose to rehabilitate urban areas and/or to mitigate disaster risk. Urban transformation projects should be realized in the cities where urbanization planning is not well-organized in the past and rapid perfunctory urbanization occurs. Selecting the appropriate urban transformation projects and prioritizing them is important in the cities where there are multiple problems such as earthquake risk, flood risk and landslide risk. Prioritization of transformation projects is a multicriteria decision making problem, in which multiple stakeholders have diverse perspectives. The fuzzy set theory enables us to make mathematical operations with the linguistic evaluations in a multicriteria decision making method. In urban transformation problems, especially for subjective criteria, stakeholders usually prefer making linguistic evaluations. When decision makers show hesitancy in their evaluations, hesitant fuzzy linguistic term sets (HFLTS) can be used to integrate various linguistic evaluations without losing any information. Istanbul is the largest metropolitan of Turkey where a probable earthquake is expected in the near future. In this paper, a new linguistic group decision making based hesitant fuzzy TOPSIS approach for evaluating urban transformation projects is proposed and a real world application for Istanbul is provided. Four urban transformation alternatives for Istanbul are prioritized by the proposed method and a sensitivity analysis is conducted.
Keywords: Multicriteria, urban transformation, linguistic term, hesitant fuzzys, TOPSIS
DOI: 10.3233/IFS-152016
Journal: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2459-2474, 2016
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