Multiple attributes group decision-making based on trigonometric operators, particle swarm optimization and complex intuitionistic fuzzy values

Rani, Dimple; Garg, Harish

doi:10.1007/s10462-022-10208-2

Cited by 22 publications

(9 citation statements)

References 43 publications

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“…In this segment, we bring in some fundamental theories associated to FSs [44,47,48], TFN, similarity measure and distance measure used in the study. [60] and Zhao and Zhang [61].…”

Section: Preliminariesmentioning

confidence: 99%

“…Fuzziness characterisation and quantification are critical concerns that influence the management of uncertainty in many information systems and concepts. Biswas et al [ 11 ] proposed a new multi-criteria decision-making (MCDM) framework with spherical fuzzy numbers, trigonometric operators [ 47 ], picture fuzzy number [ 10 , 12 ] and Fermatean fuzzy information [ 13 ]. Pamucar et al [ 44 ] developed a novel decision-making approach using Measuring attractiveness through a categorical-based evaluation technique (MACBETH) and a new combinative distance-based assessment method to address the supplier selection problem during the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

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Some distance measures for triangular fuzzy numbers under technique for order of preference by similarity to ideal solution environment

Arora

Naithani

2023

OPSEARCH

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In our daily life, we always choose to access our decisions so that we can gain greatly from them based on our prior experiences. However, it might be challenging to reach the best decision in a fair amount of time due to the complex environment and lack of information about the system due to human error these days. Triangular fuzzy numbers are proving to be quite useful in many application fields because of their apparent flexibility in coping with the imprecision or uncertainty in the process of multi criteria decision making. A technique for order preference by similarity to ideal solution presents a solution for decision-makers that are usually multi attributes and involves a complex decision-making process. It is utilized due to its ability for considering both the qualitative and quantitative measures. The goal of this paper is to employ a technique for order preference by similarity to ideal solution‐based methodology to solve multicriteria group decision‐making problems proposed for triangular fuzzy environment. Proofs of axiomatic properties for distance measures is also discussed. Sensitivity analysis is used to improve the efficacy of the proposed measures. Comparison with the present measures is also performed. Our method requires fewer calculations and produces the improved results faster than previous methods.

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“…In this segment, we bring in some fundamental theories associated to FSs [44,47,48], TFN, similarity measure and distance measure used in the study. [60] and Zhao and Zhang [61].…”

Section: Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Some distance measures for triangular fuzzy numbers under technique for order of preference by similarity to ideal solution environment

Arora

Naithani

2023

OPSEARCH

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“…For group decision-making problems, hesitant fuzzy set, complex intuitionistic fuzzy set, and probabilistic hesitant fuzzy set have been introduced to handle and model the uncertainty and vagueness in decision-making very effectively, reflect the importance of different numerical values more clearly, elicit the decision makers' knowledge, and develop more effective decision-making model. [16][17][18] Rani and Garg [16] proposed a novel algorithm for multiattribute group decision-making using complex intuitionistic fuzzy values. Jin et al [17] proposed a decision-making model using probabilistic hesitant fuzzy preference relations for reflecting clearly the importance of different numerical values and eliciting the decision makers' knowledge in the group decision-making problems.…”

Section: Introductionmentioning

confidence: 99%

Consistency Improvement Method of Pairwise Matrix Based on Consistency Ratio Decreasing Rate and Attribute Weighting Method Considered Decision Makers’ Levels in Analytic Hierarchy Process: Application to Hip Joint Prosthesis Material Selection

Yang¹,

Kang²,

Ri³

et al. 2022

Mathematical Problems in Engineering

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Analytic hierarchy process (AHP) is a well-known attribute weighting method in multiattribute decision-making. Its major requirement is to satisfy the consistency of pairwise matrix (PM). To solve this problem, we first propose a new consistency improvement method of PM based on consistency ratio (CR) decreasing rate. In this method, we calculate the CR decreasing rates of all the PMs reconstituted by replacing all elements of the PM with the lower and upper neighbouring 9-point scales and find the element with maximum CR decreasing rate, and then modify it to its lower or upper neighbouring scale. Second, we develop third-order approximate polynomial for random consistency index using least square method. It enables to determine the RI value according to the number of attributes without a numerical table. Third, we propose the final PM determining method and final attribute weighting method considered decision makers’ levels based on the CR values of the individual PMs in case several decision makers perform their own pairwise comparisons. We test the performances of the proposed and some previous consistency improvement methods with two numerical examples. The results demonstrate that the proposed method improves the consistency of PM better and faster with smaller amount of modification than that of the previous methods, while it modify the elements of the PM to 9-point scales, necessarily. We apply the proposed method to hip joint prosthesis material selection. The proposed methods may be widely used in practical applications of AHP.

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“…Multiple criteria decision analysis (MCDA) is generally delineated as an analytical process for making the most suitable choice with the highest relative dominance out of a group of candidate alternatives characterized by multiple performance criteria (Jaini 2023 ; Kaya et al 2022 ; Shen et al 2022 ). To tackle and manage real-world decision issues, numerous MCDA models, approaches, and techniques have been created and applied in a variety of application domains (Garg and Rani 2022 ; Rani and Garg 2022 ; Reig-Mullor et al 2022 ; Tiwari and Gupta 2022 ). Many MCDA systems employ a step-by-step evaluation process that entails gathering pertinent information, identifying potential alternatives, and assessing workable solutions to aid decision-makers in making more deliberate and meaningful decisions (Chen 2022a , b ; Tsao and Chen 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Evolved distance measures for circular intuitionistic fuzzy sets and their exploitation in the technique for order preference by similarity to ideal solutions

Chen

2022

Artif Intell Rev

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Circular intuitionistic fuzzy (C-IF) sets are an up-and-coming tool for enforcing indistinct and imprecise information in variable and convoluted decision-making situations. C-IF sets, as opposed to typical intuitionistic fuzzy sets, are better suited for identifying the evaluation data with uncertainty in intricate realistic decision situations. The architecture of the technique for order preference by similarity to ideal solutions (TOPSIS) provides powerful evaluation tools to aid decision-making in intuitionistic fuzzy conditions. To address appraisal issues associated with decision analysis involving extremely convoluted information, this paper propounds a novel C-IF TOPSIS approach in the context of C-IF uncertainty. This research makes three significant contributions. First, based on the three- and four-term operating rules, this research introduces C-IF Minkowski distance measures, which are new generalized representations of distance metrics applicable to C-IF values and C-IF sets. Such general C-IF distance metrics can alleviate the constraints of established C-IF distance measures, provide usage resiliency through parameter settings, and broaden the applicability of metric analysis. Second, unlike existing C-IF TOPSIS methods, this research fully utilizes C-IF information characteristics and extends the core structure of the classic TOPSIS to C-IF contexts. With the newly developed C-IF Minkowski metrics, this study faithfully demonstrates the trade-off evaluation and compromise decision rules in the TOPSIS framework. Third, this research builds on the core strengths of the pioneered C-IF Minkowski distance measures to create innovative C-IF TOPSIS techniques utilizing four different combinations, including displaced and fixed anchoring frameworks, as well as three- and four-term representations. Such a refined C-IF TOPSIS methodology can assist decision-makers in proactively addressing increasingly sophisticated decision-making problems in practical settings. Finally, this research employs two innovative prioritization algorithms to address a site selection issue of large-scale epidemic hospitals to illustrate the superior capabilities of the C-IF TOPSIS methodology over some current related approaches.

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Multiple attributes group decision-making based on trigonometric operators, particle swarm optimization and complex intuitionistic fuzzy values

Cited by 22 publications

References 43 publications

Some distance measures for triangular fuzzy numbers under technique for order of preference by similarity to ideal solution environment

Some distance measures for triangular fuzzy numbers under technique for order of preference by similarity to ideal solution environment

Consistency Improvement Method of Pairwise Matrix Based on Consistency Ratio Decreasing Rate and Attribute Weighting Method Considered Decision Makers’ Levels in Analytic Hierarchy Process: Application to Hip Joint Prosthesis Material Selection

Evolved distance measures for circular intuitionistic fuzzy sets and their exploitation in the technique for order preference by similarity to ideal solutions

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