A novel VIKOR approach based on entropy and divergence measures of Pythagorean fuzzy sets to evaluate renewable energy technologies in India

Rani, Pratibha; Mishra, Arunodaya Raj; Pardasani, Kamal Raj; Mardani, Abbas; Liao, Huchang; Štreimikienė, Dalia

doi:10.1016/j.jclepro.2019.117936

Cited by 237 publications

(113 citation statements)

References 70 publications

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“…The fuzzy VIKOR is a more useful method for solving multi-criteria GDM problems, which is a robust approach in evaluating the alternatives over conflicting criteria. Fuzzy GDM approaches play an important role using intuitionistic fuzzy information [61], Pythagorean fuzzy sets [62,63], and hesitant linguistic information [64] in different areas. A group of DMs determines the fixed ideal solution by the best (positive ideal) f * i and the worst (negative ideal) f − i values of entire criterion ratings using Equation (10), sequentially.…”

Section: Fuzzy Vikor Methodsmentioning

confidence: 99%

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

et al. 2020

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Energy systems planning commonly involves the study of supply and demand of power, forecasting the trends of parameters established on economics and technical criteria of models. Numerous measures are needed for the fulfillment of energy system assessment and the investment plans. The higher energy prices which call for diversification of energy systems and managing the resolution of conflicts are the results of high energy demand for growing economies. Due to some challenging problems of fossil fuels, energy production and distribution from alternative sources are getting more attention. This study aimed to reveal the most proper energy systems in Saudi Arabia for investment. Hence, integrated fuzzy AHP (Analytic Hierarchy Process), fuzzy VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) and TOPSIS (Technique for Order Preferences by Similarity to Idle Solution) methodologies were employed to determine the most eligible energy systems for investment. Eight alternative energy systems were assessed against nine criteria—power generation capacity, efficiency, storability, safety, air pollution, being depletable, net present value, enhanced local economic development, and government support. Data were collected using the Delphi method, a team of three decision-makers (DMs) was established in a heterogeneous manner with the addition of nine domain experts to carry out the analysis. The fuzzy AHP approach was used for clarifying the weight of criteria and fuzzy VIKOR and TOPSIS were utilized for ordering the alternative energy systems according to their investment priority. On the other hand, sensitivity analysis was carried out to determine the priority of investment for energy systems and comparison of them using the weight of group utility and fuzzy DEA (Data Envelopment Analysis) approaches. The results and findings suggested that solar photovoltaic (PV) is the paramount renewable energy system for investment, according to both fuzzy VIKOR and fuzzy TOPSIS approaches. In this context our findings were compared with other works comprehensively.

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Section: Fuzzy Vikor Methodsmentioning

confidence: 99%

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

et al. 2020

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“…can be used to represent mathematical equivalence of the linguistic variables. Fuzzy MCDM methods have been widely used by researchers to solve different types of decision problems [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Multi-Response Optimization of Nanofluid-Based I. C. Engine Cooling System Using Fuzzy PIV Method

et al. 2019

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Effective cooling of the internal combustion (I. C.) engines is of utmost importance for their improved performance. Automotive heat exchangers used as radiator with low efficiency in the industry may pose a serious threat to the engines. Thus, thermal scientists and engineers are always looking for modern methods to boost the heat extraction from the engine. A novel idea of using nanofluids for engine cooling has been in the news for some time now, as they have huge potential because of better thermal properties, strength, compactness, etc. Nanofluids are expected to replace the conventional fluids such as ethylene glycol, propylene glycol, water etc. due to performance and environmental concerns. Overall performance of the engine cooling system depends on several input parameters and therefore they need to be optimised to achieve an optimum performance. This study is focussed on developing a nanofluid engine cooling system (NFECS) where Al2O3 nanoparticles mixed with ethylene glycol (EG) and water is used as nanofluid. Furthermore, it also explores the effect of four important input parameters of the NFECS i.e., nanofluid inlet temperature, engine load, nanofluid flow rate, and nanoparticle concentration on its five attributes (output responses) viz thermal conductivity of the nanofluid, heat transfer coefficient, viscosity of the nanofluid, engine pumping power required to pump the desired amount of the nanofluid, and stability of the nanofluid. Taguchi’s L18 orthogonal array is used as the design of experiment to collect experimental data. Weighting factors are determined for output responses using the Triangular fuzzy numbers (TFN) and optimal setting of the input parameters is obtained using a novel fuzzy proximity index value (FPIV) method.

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“…Mete [37], Oz et al [38], and Pérez-Domínguez et al [39] employed an identical nine-point scale for expressing linguistic evaluations in PF settings. Rani et al [40] introduced a nine-point linguistic scale for assisting decision-makers' judgments concerning the performance evaluations of alternatives in terms of criteria. Seker and Aydin [41] provided nine-point linguistic terms and their corresponding interval-valued PF numbers that can be used for the evaluation of alternatives with criteria.…”

Section: Mcgdm Problem Under Pf Uncertaintymentioning

confidence: 99%

A Novel Pythagorean Fuzzy LINMAP-Based Compromising Approach for Multiple Criteria Group Decision-Making with Preference Over Alternatives

Wang¹,

Chen²

2020

IJCIS

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A B S T R A C TThis paper presents a new compromising approach to multiple criteria group decision-making (MCGDM) for the treatment of uncertainty which is based on Pythagorean fuzzy (PF) sets. The present work intends to propose a novel linear programming technique for multidimensional analysis of preference (LINMAP) by way of some useful concepts related to PF dominance relations, individual consistency and inconsistency levels, and individual fit measurements. The concept of PF scalar function-based dominance measures is defined to conduct intracriterion comparisons concerning uncertain evaluation information based on Pythagorean fuzziness; moreover, several valuable properties are also investigated to demonstrate its effectiveness. For the assessment of overall dominance of alternatives, this paper provides a synthetic index, named a comprehensive dominance measure, which is the aggregation of the weighted dominance measures by combining unknown weight information and PF dominance measures of various criteria. For each decision-maker, this paper employs the proposed measures to evaluate the individual levels of rank consistency and rank inconsistency regarding the obtained overall dominance relations and the decision-maker's preference comparisons over paired alternatives. In the framework of individual fit measurements, this paper constructs bi-objective mathematical programming models and then provides their corresponding parametric linear programming models for generating the best compromise alternative. Realistic applications with some comparative analyses concerning railway project investment are implemented to demonstrate the appropriateness and usefulness of the proposed methodology in addressing actual MCGDM problems.However, the classical LINMAP methods cannot be directly employed to handle the decision-making problems involving fuzzy information because of the uncertainty contained in performance information or evaluation values of candidate alternatives in terms of criteria [8][9][10]. Accordingly, numerous studies have extended the classical LINMAP for conducting multiple criteria decision analysis in a variety of different fuzzy circumstances. For example, Wan and Li [11] emanated from LINMAP to construct an intuitionistic fuzzy programming method for handling heterogeneous MCGDM containing intuitionistic fuzzy truth degrees. Furthermore, Wan and Li [8] considered the hesitancy degrees about pairwise comparisons as interval-valued intuitionistic fuzzy sets to establish a fuzzy LINMAP-based method for conducting a heterogeneous decision analysis. Zhang et al. [12] utilized the LINMAP and Shapley values to develop an interval-valued intuitionistic fuzzy mathematical programming model to manage uncertain MCGDM problems. Moreover, Zhang et al.[13] established a mathematical programming-based approach to heterogeneous MCGDM involving aspirations and incomplete preference information. Zhang and Xu [10] applied the LINMAP structure to present an interval programming method for handling MCGDM problems

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A novel VIKOR approach based on entropy and divergence measures of Pythagorean fuzzy sets to evaluate renewable energy technologies in India

Cited by 237 publications

References 70 publications

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

Multi-Response Optimization of Nanofluid-Based I. C. Engine Cooling System Using Fuzzy PIV Method

A Novel Pythagorean Fuzzy LINMAP-Based Compromising Approach for Multiple Criteria Group Decision-Making with Preference Over Alternatives

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