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Interval type-2 Fuzzy ARAS method for recycling facility location problems

  • Selman Karagöz
  • , Muhammet Deveci
  • , Vladimir Simic
  • , Nezir Aydin
  • Nottingham Trent University
  • Yildiz Technical University
  • National Defence University
  • University of Belgrade

Research output: Contribution to journalArticlepeer-review

Abstract

The management of end-of-life vehicles (ELVs) is currently one of the most important ecological topics. The recycling process has essential importance for the environmental and economic sustainability of the ELV management. Istanbul has the highest rate of car ownership population in Turkey as well as an old vehicle fleet. There is a strong motivation to open an additional ELV recycling facility in this mega-city. Facility location is one of the crucial strategic problems for decision-makers. Addressing multi-criteria and highly uncertain nature of the ELV recycling facility location problem, this paper introduces a novel approach to support the facility location process. For the first time, an extension of the Additive ratio assessment (ARAS) method under the interval type-2 fuzzy environment is presented. The novel method is utilized for solving the ELV recycling facility location problem. The potentials and applicability of the presented interval type-2 fuzzy ARAS method are demonstrated throughout the real-life case study of Istanbul. The comparison with the available state-of-the-art interval type-2 fuzzy set based MCDM methods approves its validity and consistency.
Original languageEnglish
Article number107107
Number of pages14
JournalApplied Soft Computing
Volume102
Early online date21 Jan 2021
DOIs
Publication statusPublished - Apr 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • End-of-life vehicle
  • Recycling facility location selection
  • Interval type-2 fuzzy set
  • ARAS
  • Multi-criteria decision-making

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