Multiple Attribute Decision Making Research Articles

Algorithms for multiple attribute decision making with dual hesitant Pythagorean fuzzy information and their application to supplier selection

In this paper, we investigate the multiple attribute decision making (MADM) problem based on the Hamacher aggregation operators and Choquet integral with dual Pythagorean hesitant fuzzy information. Then, motivated by the ideal of Hamacher operation and Choquet integral, we have developed some Hamacher correlated operators for aggregating dual hesitant Pythagorean fuzzy information. The prominent characteristic of these proposed operators is studied. Then, we have utilized these two operators to develop some approaches to solve the dual hesitant Pythagorean fuzzy MADM problems. Finally, a practical example for supplier selection in supply chain management is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Novel Aczel–Alsina operations-based hesitant fuzzy aggregation operators and their applications in cyclone disaster assessment

As a fuzzy set (FS) expansion, the hesitant fuzzy set (HFS) is successfully employed to demonstrate circumstances where it is admissible to ascertain a few potential membership degrees (MDs) of a component in a set because of the uncertainty between various values. Considering that there is still no research on Aczel–Alsina triangular norms and conorms in a hesitant fuzzy (HF) environment, in this article we introduce for the first time, Aczel–Alsina operations on HFSs. Then, based on these operations, we originate a few new aggregation operators for aggregating HF information namely HF Aczel–Alsina weighted averaging (HFAAWA) operator, HF Aczel–Alsina ordered weighted averaging (HFAAOWA) operator, HF Aczel–Alsina hybrid averaging (HFAAHA) operator, HF Aczel–Alsina weighted geometric (HFAAWG) operator, HF Aczel–Alsina ordered weighted geometric (HFAAOWG) operator, HF Aczel–Alsina hybrid geometric (HFAAHG) operator and HF Aczel–Alsina weighted Bonferroni mean (HFAAWBM) operator. Some essential characteristics of those suggested operators are shown, and the interrelatedness between them is displayed exhaustively. Then, we take advantage of those operators to produce a methodology to interpret the HF multiple attribute decision making (MADM) difficulties. We present a functional model for cyclone disaster assessment to certify the produced approaches and to establish their effectiveness and practicality. Further, we conduct comparison analysis for the legitimacy of our produced methodologies.

Understanding the impacts induced by cut-off thresholds and likelihood measures on confidence interval when applying GLUE approach

Generalized likelihood uncertainty estimate (GLUE) approach is affected heavily by the choice of cut-off threshold (Tr) and likelihood measure. This work presents a research on investigating potential mechanisms behind the impacts of Tr and likelihood measure on 95% confidence interval estimated by GLUE (95 CI). Several typical likelihood measures are classified into five groups according to error models. Theoretical analysis reveals strict mathematical relationships between likelihood measures based on a same error model. Besides, a multiple attribute decision making (MADM) framework is proposed to assess overall quality of various geometrical features for 95 CI by integrating a range of interval indicators into a comprehensive score. Case studies indicate that (1) As Tr increases, 95 CI widens in low-level flow section, moves upward in recession phase of medium-level flow section and narrows in high-level flow section. The variations of interval indicators with Tr can be attributed to trade-off mechanism amongst the variations of geometrical features caused by widening, moving and narrowing trends of 95 CIs. (2) Much higher similarity in interval indicators and 95 CIs occurs for likelihood measures of a same group than those of different groups. (3) Formula of likelihood measure controls individuality of 95 CIs, error model of likelihood measure controls commonality of 95 CIs, and Tr acts as a regulator between individuality and commonality. (4) 95 CI shows similar responses to the choice of Tr and likelihood measure regardless of time span and climate variability. To summarize, this work offers further understanding and guidance in chose of Tr and likelihood measure for GLUE applications.

Decision-making based on probabilistic linguistic term sets without loss of information

Probabilistic linguistic term set (PLTS) provides a much more effective model to compute with words and to express the uncertainty in the pervasive natural language by probability information. In this paper, to avoid loss of information, we redefine the classical probabilistic linguistic term sets (PLTSs) by multiple probability distributions from an ambiguity perspective and present some basic operations using Archimedean t-(co)norms. Different from the classical PLTSs, the reformulated PLTSs are not necessarily normalized beforehand for further investigations. Moreover, the multiple probability distributions based PLTSs facilitate the incorporation of the different attitudes of the DMs in their score values and the deviation, and thus the comparisons. Then the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is extended to the reformulated PLTS frame by incorporating probability information. With these newly developed elements in the reformulated PLTSs, a DEMATEL based multiple attributes decision-making is proposed. The illustrative example and comparison analysis show that the method over the reformulated PLTSs is feasible and valid, and has the advantage in processing without any information loss (i.e., without normalization) and fully exploration of the DMs-preference and knowledge.

Ranking and selection of optimum alternatives based on linear scale transformation for cylindrical roller bearing

Bearing is the most precautious element in rotating machinery. Defects produced in any part of the bearing may lead to a hazardous environment that increases the noise and vibration. It can be diminished with appropriate loading combinations. The selection of optimum loading conditions requires developing an algorithm. Multiple Attribute Decision Making (MADM) techniques are utilized to pick up a unique and ideal solution or ranking of choices from the available alternatives. The MADM techniques have not been used for bearing fault diagnosis so far. This paper offers a novel methodology for the Ranking and Selection of Optimum Alternative based on Linear Scale Transformation (RSOA-LST), having combined benefit and cost criteria that rank the choices and determine the percentage influence of various alternatives. This methodology has been performed with several experimental signals of cylindrical roller bearing, acquired from twenty-four bearing conditions having several speeds and loading combinations. The normalization of attributes (statistical features) considering combined benefit-cost criteria, mean of various parameters (speeds, attributes, and bearing conditions), and Percentage Influencing (PI) are intended simultaneously to obtain the ranking of alternatives (loading conditions). Local Defect Analysis (LDA) and Global Defect Analysis (GDA) are carried out in this research. In LDA, the ranking of alternatives based on the PI for each defect and the ranking of bearings based on fluctuation in PI of various alternatives are attained. In GDA, the sequence of alternatives is obtained globally. The effectiveness of the suggested methodology has been verified over other MADM techniques. The outcomes state that the suggested technique effectively bifurcates the influence of alternatives locally as well as globally over other techniques.

Combination of sustainability and circular economy to develop a cleaner building industry

The building construction industry is responsible for utilizing plenty of natural resources, water, and energy in the entire product life-cycle on one hand and producing air, water, and soil pollutions particularly in the operation phase on the other hand. Thus, regarding the high frequency of these projects, it is important to develop an integrated assessment framework to consider both sustainability in the development and circuity in the economy to ensure a cleaner building industry. This study aims to combine Sustainability and Circular Economy as two critical performance criteria in the context of building industry projects in order to move toward the integrated assessment model. Since the Circular Economy (CE) is related to a cradle-to-cradle life-cycle approach, the Prospective Multiple Attribute Decision Making (PMADM) utilities are utilized in this study. Afterward, an empirical study is used to weigh up the framework and assess different locations as an application of the proposed model. In this regard, two different mathematical approaches are used to ensure the reliability of the weigh-up results (Analytical Hierarchy Process (AHP) and Indifference Threshold-based Attribute Ratio Analysis (ITARA)). Finally, the case study alternatives are evaluated based on the weighted integrated framework by using Combined Compromise Solution (CoCoSo). As a result, these two different mathematical approaches successfully converged and confirmed the results and ratings. Also, the integrated framework ensures both sustainability and local environmental resiliency in developing the building industry projects simultaneously.

Harmonic Aggregation Operator with Trapezoidal Picture Fuzzy Numbers and Its Application in a Multiple-Attribute Decision-Making Problem

Picture fuzzy sets (PFSs) can be used to handle real-life problems with uncertainty and vagueness more effectively than intuitionistic fuzzy sets (IFSs). In the process of information aggregation, many aggregation operators under PFSs are used by different authors in different fields. In this article, a multi-attribute decision-making (MADM) problem is introduced utilizing harmonic mean aggregation operators with trapezoidal fuzzy number (TrFN) under picture fuzzy information. Three harmonic mean operators are developed namely trapezoidal picture fuzzy weighted harmonic mean (TrPFWHM) operator, trapezoidal picture fuzzy order weighted harmonic mean (TrPFOWHM) operator and trapezoidal picture fuzzy hybrid harmonic mean (TrPFHHM) operator. The related properties about these operators are also studied. At last, an MADM problem is considered to interrelate among these operators. Furthermore, a numerical instance is considered to explain the productivity of the proposed operators.

4 Star Complementary Food Menu Recommendation System Using the Mobile-Based Fuzzy Multiple Attribute Decision Making (FMADM) Method

Toddler in the age category of six to twenty-four months should be ready to be given complementary food. In order to fulfill the nutritional needs for the toddler's growth, complementary foods must be sufficient for the kid according to their age while still paying attention to the continuity of breastfeeding. One thing that must be considered in choosing complementary foods is the Recommended Dietary Allowances (RDA) which is categorized by age, weight, and food texture, which is adjusted to the toddler age category. In terms of fulfilling all aspects of choosing complementary foods, this study proposes the design of a 4-star daily menu recommendation system for toddlers which refers to the intake of daily calorie needs for toddlers, namely carbohydrates, animal protein, vegetable protein, and vitamins/minerals using the FMADM method (Fuzzy Multiple Attribute Decision Making). The FMADM method used is the Electre method. In this study, the authors succeeded in building the desired recommendation system using the Electre method which produces a daily menu based on the number of mealtimes, based on the age and weight of toddlers by observing the user's tendency to the texture and composition of food and its nutritional content in the recommendation system that is built, so that can be accessed via mobile devices owned by the user.

Evaluation Model of Highway Reconstruction and Expansion Scheme Based on Multiple Attribute Decision Making

The renovation and expansion of highway is a technical, comprehensive, and complex work, and the determination of its optimal scheme requires the consideration of multiple factors. In the process of highway construction, road engineers attempt to select an optimal scheme with the aim of saving cost, reducing construction difficulties, and protecting environment. It is difficult to assess because of the large number of attribute indices and the diversity of data distribution. In order to scientifically evaluate the comprehensive benefits of highway reconstruction and extension (HRE) schemes, an evaluation model of HRE scheme based on multiple attribute decision making (MADM) was established. This paper constructed the evaluation index system of HRE based on the four aspects of technology, economy, environmental impact, and landscape. This paper has made two major improvements. First, a method was proposed to determine the weight of evaluation index by coupling fuzzy analytic hierarchy process (FAHP) with difference driven principle (DDP). Then, technique for order preference by similarity to an ideal solution (TOPSIS) method was optimized by grey relational analysis (GRA) method. Finally, the MADA evaluation model is utilized to analyze the ranking of optimal scheme selection problem by relative closeness as a decision index. The results showed that the subjective intention of decision makers was considered and also fully the objective information of data itself was fully mined. The optimal scheme was scheme 3 through the analysis of five HRE schemes. This model highlighted the differences among the schemes and also avoided the problem of excessive differences. The results were consistent with the actual situation, verifying the feasibility and practicability of the model.

A Novel SIR Approach to Closeness Coefficient‐Based MAGDM Problems Using Pythagorean Fuzzy Aczel–Alsina Aggregation Operators for Investment Policy

In this study, a novel Pythagorean fuzzy aggregation operator is presented by combining the concepts of Aczel–Alsina () T‐norm and T‐conorm operations for multiple attribute group decision‐making (MAGDM) challenge for the superiority and inferiority ranking (SIR) approach. This approach has many advantages in solving real‐life problems. In this study, the superiority and inferiority ranking method is illustrated and showed the effectiveness for decision makers by using multicriteria. The Aczel–Alsina aggregation operators on interval‐valued IFSs, hesitant fuzzy sets (HFSs), Pythagorean fuzzy sets (PFSs), and T‐spherical fuzzy sets (TSFSs) for multiple attribute decision‐making (MADM) issues have been proposed in the literature. In addition, we propose a Pythagorean fuzzy Aczel–Alsina weighted average closeness coefficient () aggregation operator on the basis of the closeness coefficient for MAGDM challenges. To highlight the relevancy and authenticity of this approach and measure its validity, we conducted a comparative analysis with the method already in vogue.

Retracted] A Decision‐Making Framework for University Student Sports Study Psychological Healthy Evaluation with 2‐Tuple Linguistic Neutrosophic Numbers

A healthy body is the foundation of education, and the guiding ideology of health first requires that all educational work in schools should take the health of students as the starting point and be responsible for the health of students. Taking the development of students as the foundation, its essential meaning is to make students develop into a “complete person,” that is, to integrate and unify students’ morality, intelligence, physique, beauty, life, habits, morality, skills, and other elements. The establishment of the evaluation index system of sports health literacy is a complex evaluation system with multiple factors and multiple indicators. The university student sports study psychological healthy evaluation is always looked as the multiple attribute decision‐making (MADM) issue. In this paper, based on the generalized Heronian mean (HM) operator and generalized weighted HM (GWHM) operator, the generalized 2‐tuple linguistic neutrosophic HM (G2TLNHM) operator and generalized 2‐tuple linguistic neutrosophic weighted HM (G2TLNWHM) operator are proposed with 2‐tuple linguistic neutrosophic sets (2TLNSs). Finally, an example of university student sports study psychological healthy evaluation is used to show the proposed methods. Some comparative studies and parameter influence analysis on the final result are fully given. The results show that the built algorithms method is really useful for university student sports study psychological healthy evaluation.

Multiple attribute decision making for square root diophantine neutrosophic interval-valued sets and their aggregated operators

Square root Diophantine neutrosophic interval-valued set (SRDioNIVS) approaches to multiple attribute decisionmaking (MADM) problems. The square root neutrosophic sets, interval-valued Diophantine neutrosophic sets are both extensions of square root Diophantine neutrosophic sets. In this section, we discuss aggregating operations and how those interprtautions have evolved over time. The paper is focused on a novel idea known as square root neutrosophic interval-valued weighted averaging (SRDioNIVWA), square root neutrosophic interval-valued weighted geometric (SRDioNIVWG), generalized square root neutrosophic interval-valued weighted averaging (GSRDioNIVWA), and generalized square root neutrosophic interval-valued weighted geometric (GSRDioNIVWG). We also begin an algorithm using these operators. The use of the euclidean and hamming distances is described, and examples from real-world problems are inserted. As a result, the defined models are more accurate and closely tied to Ξ. In order to show the reliability and usefulness of the models under examination, we also compare a few of the proposed and current models. The study’s results are also fascinating and intriguing.

Square root Diophantine neutrosophic normal interval-valued sets and their aggregated operators in application to multiple attribute decision making

We discuss innovative square root Diophantine neutrosophic normal interval-valued set (SRDioNSNIVS)- based approaches to multiple attribute decision-making (MADM) problems. Square root neutrosophic sets, interval-valued Diophantine neutrosophic sets and neutrosophic normal interval-valued (NSNIV) sets are both extensions of square root Diophantine neutrosophic sets. In this section, we will look over several aggregating operations and how those interpretations have evolved over time. The article is focused on a novel idea known as square root NSNIV weighted averaging (SRDioNSNIVWA), square root NSNIV weighted geometric (SRDioNSNIVWG), generalized square root NSNIV weighted averaging (GSRDioNSNIVWA), and generalized square root NSNIV weighted geometric (GSRDioNSNIVWG). In order to solve MADM problems, we also begin an algorithm based on the aforementioned operators. The use of the euclidean and hamming distances is described, and examples from real-world situations are given. The main characteristics of these sets under various algebraic operations will be discussed in this communication. They are more practical and straightforward, and the ideal choice may be determined quickly. As a result, the defined models are more accurate and closely tied to Φ. In order to show the reliability and usefulness of the models under examination, we also compare a few of the proposed and current models. The study’s results are also fascinating and intriguing.

Applications of Cubic Schweizer–Sklar Power Heronian Mean to Multiple Attribute Decision‐Making

The cubic set (CS) is a basic simplification of several fuzzy notions, including fuzzy set (FS), interval‐valued FS (IVFS), and intuitionistic FS (IFS). By the degrees of IVFS and FS, CS exposes fuzzy judgement, and this is a much more potent mathematical approach for dealing with information that is unclear, ambiguous, or indistinguishable. The article provides many innovative operational laws for cubic numbers (CNs) drawn on the Schweizer–Sklar (SS) t‐norm (SSTN), and the SS t‐conorm (SSTCN), as well as several desired properties of these operational laws. We also plan to emphasise on the cubic Schweizer–Sklar power Heronian mean (CSSPHM) operator, as well as the cubic Schweizer–Sklar power geometric Heronian mean (CSSPGHM) operator, in order to maintain the supremacy of the power aggregation (PA) operators that seize the complications of the unsuitable information and Heronian mean (HM) operators that contemplate the interrelationship between the input data being aggregated. A novel multiple attribute decision‐making (MADM) model is anticipated for these freshly launched aggregation operators (AOs). Finally, a numerical example of enterprise resource planning is used to validate the approach’s relevance and usefulness. There is also a comparison with existing decision‐making models.

An Extended Hesitant Fuzzy Set for Modeling Multi-Source Uncertainty and its Applications in Multiple-Attribute Decision-Making

An Extended Hesitant Fuzzy Set for Modeling Multi-Source Uncertainty and its Applications in Multiple-Attribute Decision-Making

An Efficient Hybrid Ranking Method for Cloud Computing Services Based on User Requirements

An increase in the number of cloud services makes service selection a challenging issue for cloud users. It is important to determine the best service that can fulfill user requirements. To this end, this paper proposes a hybrid multiple-attribute decision-making (MADM) model. The proposed method considers service measurement index cloud (SMICloud) structure for qualitative attributes of cloud services as well as user requirements based on fuzzy values to consider vague user requirements. Analytical hierarchy process (AHP) and fuzzy logic are used to rank cloud services. Furthermore, a fuzzy Delphi filtering method is proposed to decrease the execution time of ranking cloud services. In experiments, different aspects such as accuracy, execution time, scalability, and sensitivity analysis are investigated. The results confirm that the proposed method outperforms available methods in terms of execution time and scalability. Furthermore, the experiments show that the proposed method has achieved an accuracy of 96%.

Novel operations of weighted hesitant fuzzy sets and their group decision making application

<abstract><p>Weighted hesitant fuzzy set (WHFS) is an extension of hesitant fuzzy set (HFS), in which the weights indicate that the decision maker has different confidence in giving every possible assessment of the membership degree. In this paper, we redefine the union and intersection operations of weighted hesitant fuzzy elements (WHFEs), investigate their operation properties, and propose the variance function of the weighted hesitant fuzzy element (WHFE) to compare WHFEs. Furthermore, we develop two aggregation operators such as weighted hesitant fuzzy ordered weighted averaging (WHFOWA) and weighted hesitant fuzzy ordered weighted geometric (WHFOWG) operators to aggregate weighted hesitant fuzzy information, and present multiple-attribute group decision making algorithm under weighted hesitant fuzzy environment. Finally, four numerical examples are used to illustrate the effectiveness of our proposed aggregation operators.</p></abstract>

Cotangent Similarity Measure of Consistent Neutrosophic Sets and Application to Multiple Attribute Decision-Making Problems in Neutrosophic Multi-Valued Setting

A neutrosophic multi-valued set (NMVS) is a crucial representation for true, false, and indeterminate multi-valued information. Then, a consistent single-valued neutrosophic set (CSVNS) can effectively reflect the mean and consistency degree of true, false, and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in NMVS. However, there has been no research on consistent single-valued neutrosophic similarity measures in the existing literature. This paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued setting. The cosine similarity measures show the cosine of the angle between two vectors projected into a multidimensional space, rather than their distance. The cotangent similarity measures in this study can alleviate several shortcomings of cosine similarity measures in vector space to a certain extent. Then, a decision-making approach is presented in view of the established cotangent similarity measures in the case of NMVSs. Finally, the developed decision-making approach is applied to selection problems of potential cars. The proposed approach has obtained two different results, which have the same sort sequence as the compared literature. The decision results prove its validity and effectiveness. Meantime, it also provides a new manner for neutrosophic multi-valued decision-making issues.

Aczel-Alsina Weighted Aggregation Operators of Simplified Neutrosophic Numbers and Its Application in Multiple Attribute Decision Making

Aczel-Alsina Weighted Aggregation Operators of Simplified Neutrosophic Numbers and Its Application in Multiple Attribute Decision Making

An Integrated Framework for Agricultural Non-Point Source Pollution Control Technology Evaluation: Application of an Improved Multiple Attribute Decision Making Method

An Integrated Framework for Agricultural Non-Point Source Pollution Control Technology Evaluation: Application of an Improved Multiple Attribute Decision Making Method