A Novel Spherical Fuzzy Bi-Objective Linear Assignment Method and Its Application to Insurance Options Selection


Seyfi-Shishavan S. A., Gundogdu F. K., Donyatalab Y., Farrokhizadeh E., Kahraman C.

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, cilt.20, sa.2, ss.521-551, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20 Sayı: 2
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1142/s0219622021500073
  • Dergi Adı: INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.521-551
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Spherical fuzzy sets are the latest extension of the ordinary fuzzy sets. The main characteristic of the spherical fuzzy sets is satisfying the condition that the squared sum of the membership, nonmembership, and hesitancy degrees must be at least zero and at most one. In this research, by extending the classical linear assignment method to bi-objective linear assignment and integrating it with cosine similarity measure, we presented a novel benecial method for solving multiple criteria group decision-making problems in the spherical fuzzy environment. A new concept for weighting the criteria, which is composed of positive and negative impacts (weights), is introduced. The proposed bi-objective model tries to maximize positive impacts and minimize the negative impacts simultaneously. In order to solve the bi-objective linear assignment model, epsilon-constraint method is applied. Therefore, a trade-off solution is formed between maximizing positive impacts and minimizing negative impacts. The applicability and validity of the proposed method are shown through an insurance options selection problem. To test the reliability and validity of the proposed method, comparative and sensitivity analysis are performed.