A novel multicriteria decision‐making approach with unknown weight information under q‐ rung orthopair fuzzy environment

Abstract

The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method has been developed as one of the effective techniques to accomplish the best alternative selection of multicriteria decision-making (MCDM) problems. However, the existing PROMETHEE methods fail to adjust the representation range of uncertain information. Moreover, the weight determination and information aggregation in the PROMETHEE model still suffer from an excessive dependence of decision makers' (DMs') subjective judgments and the lack of considering the interrelationship among criteria. To solve the aforementioned drawbacks and provide DMs with a reliable and robust method of MCDM, a novel PROMETHEE method based on the q-rung orthopair fuzzy sets, that is, q-ROF-PROMETHEE model, is presented herein.First, the PROMETHEE-II method is extended to q-rung orthopair fuzzy (q-ROF) environment, which not only handles the uncertainty of human cognition but also provides DMs with a broader space to represent their decisions information. Second, a new optimization model is constructed based on the proposed cross entropy and q-ROF entropy, which is capable of leveraging the preference of DMs to obtain the optimal objective weights among criteria. In

A q-rung orthopair fuzzy combined compromise solution approach for selecting sustainable third-party reverse logistics provider

“…A combined methodology based on the score function, q-ROF similarity measure and "weighted aggregated sum product assessment (WASPAS)" has been developed by Rani and Mishra (2020a). Recently, Zhang et al (2021) put forward a hybridized MCDA methodology using entropy, cross entropy and the classical "Preference ranking organization method for enrichment evaluation (PROMETHEE)" approach with q-ROFSs and employed for a hospital performance assessment. Xiao et al (2022) gave a novel score function to compare the q-ROF values.…”

A Lance Distance-Based MAIRCA Method for q-Rung Orthopair Fuzzy MCDM with Completely Unknown Weight Information

“…In the q-ROF context, apart from the development of various aggregation operators (Peng and Luo, 2021;Saha et al, 2022a), the alternative ranking techniques have become one of the focuses of many scholars. So far, various types of decision-making techniques have been extended and utilized in the q-ROF environment, and these methods can be classified according to their characteristics as: (1) the distance-based methods, such as TOPSIS (Dincer et al, 2022;Pinar et al, 2021;Ye et al, 2021;Alkan and Kahraman, 2021;Pinar and Boran, 2020;Khan et al, 2021b), TODIM (Krishankumar et al, 2021;Chen et al, 2021;Arya and Kumar, 2021;Liu et al, 2021;Wang and Li, 2018), VIKOR (Khan et al, 2021a;Sun et al, 2021), CODAS (Deveci et al, 2022a), EDAS (Darko and Liang, 2020;Liang et al, 2023), andMABAC (Gong et al, 2020;Wang et al, 2020a); (2) the utility-based approaches, such as WASPAS (Deveci et al, 2022b;Xiao et al, 2022), ARAS (Mishra and Rani, 2021), COPRAS (Krishankumar et al, 2019) and MARCOS (Ali, 2022); (3) the distance-and utility-based hybrid approaches, such as MULTIMOORA (Mishra et al, 2022;Riaz et al, 2022;Aydemir and Gunduz, 2020), PROMETHEE Akram and Shumaiza, 2021;Zhang et al, 2021b), DNMA (Saha et al, 2022b), CoCoSo (Deveci et al, 2022c), and GLDS Liao et al, 2020); (4) other methods, such as ORESTE (Long and Liao, 2021) and Thermodynamic Zhang et al, 2021a). These aforementioned decision-making approaches have been widely applied to handle complex decision i...…”