Ranking using PROMETHEE when weights and thresholds are imprecise: A data envelopment analysis approach


KARASAKAL E., Eryilmaz U., Karasakal O.

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, cilt.73, sa.9, ss.1978-1995, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 73 Sayı: 9
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/01605682.2021.1963195
  • Dergi Adı: JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, IBZ Online, International Bibliography of Social Sciences, Periodicals Index Online, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Sayfa Sayıları: ss.1978-1995
  • Anahtar Kelimeler: Multicriteria, data envelopment analysis, PROMETHEE, decision support systems, DECISION-MAKING UNITS, CROSS-EFFICIENCY, INTERACTIVE APPROACH, DEA, CRITERIA, INFORMATION, HIERARCHY
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Multicriteria decision making (MCDM) provides tools for the decision makers (DM) to solve complex problems with multiple conflicting criteria. Scalarization of criteria values requires using weights for criteria. Determining weights creates controversy as they are influential on the final ranking and challenges the DM as they are hard to elicit. PROMETHEE method is widely used in MCDM for ranking the alternatives and appropriate in situations when there is limited information on the preference structure of the DM. The DM should provide exact values for parameters such as criteria weights and thresholds of preference functions. Data Envelopment Analysis (DEA) is used for measuring the relative efficiency of alternatives in a non-parametric way without requiring any weight input. In this study, we propose two novel PROMETHEE based ranking approaches that address the determination of weight and threshold values by using an approach inspired by DEA. The first approach can deal with imprecise specification of criteria weights, and the second approach can utilize both imprecise weights and thresholds. The proposed approaches provide the DM substantial flexibility on the required level of information on those parameters. An illustrative example and a real-life case study are presented to show the utility of the proposed approaches.