Evaluation of Clean Energy Alternatives with Hesitant Fuzzy Linguistic MCDM Methods


MUKUL E., GÜLER KESMEZ M., Büyüközkan G.

International Conference on Intelligent and Fuzzy Systems, INFUS 2021, İstanbul, Türkiye, 24 - 26 Ağustos 2021, cilt.307, ss.325-332 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 307
  • Doi Numarası: 10.1007/978-3-030-85626-7_39
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.325-332
  • Anahtar Kelimeler: Clean energy, Hesitant fuzzy linguistic term sets, HFL AHP, HFL EDAS, MCDM
  • Galatasaray Üniversitesi Adresli: Evet

Özet

© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Energy is an indispensable resource for a country, which means stability, development, prosperity and increased quality of life. Due to the increased demand, limited natural resources, and environmental problems, clean energy resources utilization has become very important. Therefore, countries are seeking ways for using their energy resources effectively. However, several criteria have to be considered when evaluating the clean energy alternatives. For this reason, in this paper, it is constructed as a Hesitant Fuzzy Linguistic (HFL) Multi Criteria Decision Making (MCDM) problem. Hesitant Fuzzy Linguistic Term Sets (HFLTS) technique is applied to represent Decision Makers’ (DMs’) assessments by addressing the efforts on stating the ideas via crisp numbers and the uncertainty. In this context, the objective of this paper is proposing a framework for evaluating clean energy alternatives with HFL MCDM methods. The evaluation criteria weights are found by HFL Analytic Hierarchy Process (AHP) and then, clean energy alternatives are assessed by HFL Evaluation Based on Distance from Average Solution (EDAS) method. An application about this evaluation problem is presented to demonstrate the potential of the proposed framework. Finally, the application's findings are presented, as well as future directions.