A Robust q-Rung Orthopair Fuzzy Information Aggregation Using Einstein Operations with Application to Sustainable Energy Planning Decision Management

Riaz, Muhammad; Sałabun, Wojciech; Farid, Hafiz Muhammad Athar; Ali, Nazar; Wątróbski, Jarosław

doi:10.3390/en13092155

Cited by 94 publications

(69 citation statements)

References 146 publications

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“…Kizielewicz et al [22] identified a set of criteria for solving a windfarm location selection problem. Riaz et al [23] introduced a decision support system for sustainable energy planning decision management based on q-rung orthopair fuzzy set (q-ROFS). The proposed approach was applied to a sustainable energy planning problem in Pakistan in order to demonstrate the plan's feasibility and validity.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of Wave Energy Location by Using an Integrated MCDM Approach

2021

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In recent years, sudden global energy demand has led to the gradual exhaustion of fossil fuel, the world’s main energy resource. With the negative impact of fossil fuel on the environment, governments and organizations have increased R&D funding on renewable energy resources such as solar and wave energy. Vietnam has a great potential for developing wave energy projects owing to the presence of a long coastline and vast ocean. Choosing an optimal location for wave-based power plant projects is a multicriteria decision that requires understanding the quantitative and qualitative elements for assessing the balance of factors when trying to reach the most accurate result. This study proposes a multi-criteria decision-making (MCDM) model, fuzzy-analytic hierarchical process (FAHP), and weighted aggregated sum product assessment (WASPAS) in evaluating potential wave energy stations at the Vietnamese coastline. The authors identify all criteria and sub-criteria affecting the wave power plant location selection process through literature review and expert interview. Selection criteria include wave height, the distance between two waves, number of waves, wind speed, wind duration, ocean depth, turbulence, water quality, coastal erosion, shipping density, protection laws, labor resources, safety conditions, and other related factors. FAHP was used to determining the weights of the identified criteria in the first stage of this study. Finally, the WASPAS model was employed to rank all the alternatives involved in making an effective decision. This study aimed to develop a tool to enhance decision-making when solving fuzzy multi-criteria problems. We propose a real-world model for the effectiveness of the proposed model.

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Section: Literature Reviewmentioning

confidence: 99%

Evaluation of Wave Energy Location by Using an Integrated MCDM Approach

2021

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“…Riaz et al [48][49][50][51] introduced the concepts of q-rung orthopair fuzzy prioritized aggregation operators, q-rung orthopair fuzzy hybrid aggregation operators, q-rung orthopair fuzzy information aggregation using Einstein operations, q-rung orthopair fuzzy Einstein prioritized aggregation operators with application towards multi-criteria group decision making (MCGDM). Aggregation operators and MCDM methods have been studied by; Xu [52], Xu and Cai [53], Xu [54], Yager [55], Ye [56,57], Zhan et al [58,59], Zhang and Zhan [60,61], Zhang et al [62], and Harrison et al [5].…”

Section: And Degree Of Indefiniteness Is Given By πmentioning

confidence: 99%

q-Rung Orthopair Fuzzy Geometric Aggregation Operators Based on Generalized and Group-Generalized Parameters with Application to Water Loss Management

et al. 2020

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The notions of fuzzy set (FS) and intuitionistic fuzzy set (IFS) make a major contribution to dealing with practical situations in an indeterminate and imprecise framework, but there are some limitations. Pythagorean fuzzy set (PFS) is an extended form of the IFS, in which degree of truthness and degree of falsity meet the condition 0≤Θ˘2(x)+K2(x)≤1. Another extension of PFS is a q´-rung orthopair fuzzy set (q´-ROFS), in which truthness degree and falsity degree meet the condition 0≤Θ˘q´(x)+Kq´(x)≤1,(q´≥1), so they can characterize the scope of imprecise information in more comprehensive way. q´-ROFS theory is superior to FS, IFS, and PFS theory with distinguished characteristics. This study develops a few aggregation operators (AOs) for the fusion of q´-ROF information and introduces a new approach to decision-making based on the proposed operators. In the framework of this investigation, the idea of a generalized parameter is integrated into the q´-ROFS theory and different generalized q´-ROF geometric aggregation operators are presented. Subsequently, the AOs are extended to a “group-based generalized parameter”, with the perception of different specialists/decision makers. We developed q´-ROF geometric aggregation operator under generalized parameter and q´-ROF geometric aggregation operator under group-based generalized parameter. Increased water requirements, in parallel with water scarcity, force water utilities in developing countries to follow complex operating techniques for the distribution of the available amounts of water. Reducing water losses from water supply systems can help to bridge the gap between supply and demand. Finally, a decision-making approach based on the proposed operator is being built to solve the problems under the q´-ROF environment. An illustrative example related to water loss management has been given to show the validity of the developed method. Comparison analysis between the proposed and the existing operators have been performed in term of counter-intuitive cases for showing the liability and dominance of proposed techniques to the existing one is also considered.

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“…They also used their proposed methodology for DM, medical diagnoses, and pattern recognition, and developed operational laws, presented some prioritized AOs under the linguistic IFS environment [23], and extended the Maclaurin symmetric mean (MSM) operators to IFSS based on Archimedean T-conorm and T-norm [24]. Riaz et al [25] developed some AOs using Einstein Operations with desirable properties and established a MCDM method to solve DM complications. Faizi et al [26] presented a novel MCDM technique using normalized, interval-valued, triangular fuzzy numbers, and applied it to solve DM complications.…”

Section: Introductionmentioning

confidence: 99%

TOPSIS Method Based on Correlation Coefficient under Pythagorean Fuzzy Soft Environment and Its Application towards Green Supply Chain Management

et al. 2021

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The correlation coefficient between two variables is an important aspect of statistics. The accuracy of assessments of correlation relies on information from a set of discourses. Data collected in statistical studies are often full of exceptions. Pythagorean fuzzy soft sets (PFSS) are a parametrized family of extended Pythagorean fuzzy sets (PFS). They comprise a generalization of intuitionistic fuzzy soft sets which may be used to accurately assess deficiencies and uncertainties in evaluations. PFSS can accommodate uncertainty more competently than intuitionistic fuzzy soft sets and are the most important strategy when dealing with fuzzy information in decision-making processes. Herein, the concept and characteristics of correlation coefficients and the weighted correlation coefficients in PFSS are discussed. We also introduce the Pythagorean fuzzy soft weighted average (PFSWA) and Pythagorean fuzzy soft weighted geometric (PFSWG) operators and discuss their desirable characteristics. A prioritization technique for order preference by similarity to the ideal solution (TOPSIS) under the PFSS environment based on correlation coefficients and weighted correlation coefficients will be introduced. Through the proposed methodology, a technique for decision-making is developed. Additionally, an application of the proposed TOPSIS technique is presented for green supplier selection in green supply chain management (GSCM). The practicality, efficacy, and flexibility of the proposed approach is proved through comparative analyses, drawing upon existing studies.

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A Robust q-Rung Orthopair Fuzzy Information Aggregation Using Einstein Operations with Application to Sustainable Energy Planning Decision Management

Cited by 94 publications

References 146 publications

Evaluation of Wave Energy Location by Using an Integrated MCDM Approach

Evaluation of Wave Energy Location by Using an Integrated MCDM Approach

q-Rung Orthopair Fuzzy Geometric Aggregation Operators Based on Generalized and Group-Generalized Parameters with Application to Water Loss Management

TOPSIS Method Based on Correlation Coefficient under Pythagorean Fuzzy Soft Environment and Its Application towards Green Supply Chain Management

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