Fuzzy Multiple Attribute Decision Research Articles

Key performance indicators of construction companies in branding products and construction projects for success in a competitive environment in Iran

PurposeKey performance indicators (KPIs) play a pivotal role in evaluating the level of success of an organization in achieving its business objectives. The objective of the current research is to identify and prioritize effective KPIs in branding products and construction projects, which contribute to the success of construction companies in a competitive environment.Design/methodology/approachThe present research is of an inferential, descriptive and survey nature. In this study, we identified the influential key performance indicators of construction companies in branding products and construction projects for success in a competitive environment through a literature review and expert opinions. The data were collected using a questionnaire, and a combination of the one-sample t-test method with a 95% confidence level and the fuzzy multiple attribute decision-making (FMADM) method was employed for analysis.FindingsThe results indicate that the most influential key performance indicators for construction companies in branding products and construction projects for success in a competitive environment are, in order of significance, the following indices: “Marketing and Advertising,” “Financial,” “Creativity,” “Technical and Operational” and “Social and Political.”Originality/valueThe present research examines the importance of branding construction products and projects for the success of construction companies by improving their business objectives and utilizing key performance indicators throughout the product lifecycle (production and construction). This study provides solutions on how construction companies can increase their competitive advantage through branding and achieve long-term success in the global construction industry.

Research on the urban green transportation development level evaluation based on the triangular pythagorean fuzzy multiple attribute decision making

With the acceleration of urbanization and the significant improvement of people’s living standards, the motorization of urban transportation in China has developed rapidly, and the number of urban motor vehicles has sharply increased. This has also caused a series of problems such as increasingly severe urban road traffic congestion, increased traffic energy consumption, and atmospheric environmental pollution. Unprecedented social and environmental pressures have put forward higher requirements for the development model of urban transportation. Against the backdrop of increasingly severe conflicts between urban transportation and resource environment in China, green transportation with the goal of “meeting maximum demand with minimum consumption” has gradually received widespread attention from the academic community. The urban green transportation development level evaluation is a classical multiple attribute decision making (MADM). In this paper, we define the triangular Pythagorean fuzzy sets (TPFSs) and investigate the MADM problems under TPFSs. Based on the traditional geometric BM (GBM) operator and generalized weighted GBM (GWGBM) operator, some triangular Pythagorean fuzzy operators are proposed: triangular Pythagorean fuzzy generalized GBM (TPFGGBM) operator and triangular Pythagorean fuzzy generalized WGBM (TPFGWGBM) operator. Accordingly, we have took advantage of these operators to develop some approaches to work out the triangular Pythagorean fuzzy MADM. Ultimately, a practical example for urban green transportation development level evaluation is took advantage of to validate the developed approach, and an influence analysis of the parameter on the final results is been presented to attest its availability and validity.

Method for Triangular Fuzzy Multiple Attribute Decision Making Based on Two-Dimensional Density Operator Method

Method for Triangular Fuzzy Multiple Attribute Decision Making Based on Two-Dimensional Density Operator Method

An intelligent decision methodology for triangular Pythagorean fuzzy MADM and applications to college English teaching quality evaluation

Abstract The development of contemporary college English teaching methods and practice should respect the subjective will of college students; fully tap their wisdom and potential; constantly innovate college English teaching methods, teaching practice activities, classroom teaching, and teaching evaluation models; create a good teaching atmosphere; and establish the concept of developmental evaluation. Through the innovation of teaching methods, college students’ actual language communication ability is cultivated, the teaching objectives and teaching methods of college English reading are innovated, and interactive, body language, role play, situational teaching, communicative teaching, and other teaching methods are used. The College English teaching quality evaluation is a classical multiple attribute decision making (MADM). In this article, the triangular Pythagorean fuzzy sets (TPFSs) are introduced, and the MADM problem is investigated under TPFSs. Based on the traditional dual generalized weighted Bonferroni mean operator and power average operator, the triangular Pythagorean fuzzy dual generalized power Bonferroni mean (TPFDGPBM) operator is proposed. Accordingly, the TPFDGPBM operator is employed to construct the triangular Pythagorean fuzzy MADM method. Finally, a numerical example for College English teaching quality evaluation is constructed to verify the TPFDGPBM technique.

Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting for Supplier Measurement In Furniture Business

This study delves into the complexities of supplier selection in the furniture industry, where Decision Support Systems play a pivotal role in achieving data-driven, sustainable supplier choices. It underscores the Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting approach, particularly emphasizing Price, response time, and delivery fees as critical factors. The overarching objective is to elevate supplier selection in alignment with furniture companies' specific requirements and strategic goals. Additionally, the Supplier Ranking System leverages Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting techniques, ranking the third Supplier as the top Supplier with a high preference score of 0.90 and the fourth Supplier as the lowest-ranked Supplier with a score of 0.50. Notably, User Acceptance Tests affirm the System's outstanding performance and intense user satisfaction.

A hybrid intelligent model based on logistic regression and fuzzy multiple-attribute decision-making for credit evaluation

. One of the crucial issues in data mining is to select an appropriate classification algorithm. Due to it usually involves many criteria, the duty of algorithm selection can be widely described as multiple-attribute decision-making (MADM) problems, including credit risk evaluation. Many different MADM approaches select classifiers based on different perspectives, and hence they might generate diverse classifiers' rankings. This paper aims to propose a hybrid intelligent model to overcome credit risk assessment problems based on logistic regression and the fuzzy MADM method. Firstly, the Ordinal Priority Approach (OPA) method evaluates attributes involved in credit risk problems by considering professional assessments of a decision-maker and calculates a weight for each criterion. Secondly, all categorical data converted into triangular-fuzzy numbers (TFNs) and numerical data are evaluated using the MADM instrument to obtain an optimal solution dataset and logistic regression to calculate the probabilities of the optimal dataset. In this experimental study, three existing classification techniques and the proposed intelligent model evaluate three banking credit datasets with a different number of criteria under numerical and categorical data types. The prediction accuracy results generated by the proposed model are compared with the three existing classification methods. The results exhibit that there are slight differences between the three datasets. The experimental results demonstrate the proposed intelligent model has superiority in classifying the credit loan recipients especially for categorical datasets.

Grey relational analysis for online and offline blended teaching effectiveness evaluation of college English based on triangular fuzzy neutrosophic MADM

The traditional offline classroom is no longer suitable for the current situation of college English classrooms. The application of the “hybrid” teaching model in online and offline college English teaching is the trend and the focus of local higher education reform. Nowadays, many universities at home and abroad have successively established online platforms and launched online courses, striving for seamless connection between online and offline classrooms. It can be seen that exploring the “blended” teaching mode of online and offline in local higher education institutions is a trend of the times and the current situation of English language classrooms in universities. The online and offline blended teaching effectiveness evaluation of college English courses is regarded as multiple-attribute decision-making (MADM). In this paper, the triangular fuzzy neutrosophic numbers grey relational analysis (TFNN-GRA) method is designed for MADM based on the classical point GRA and triangular fuzzy neutrosophic sets (TFNSs). Finally, a numerical example for online and offline blended teaching effectiveness evaluation of college English courses is given and some comparisons are done to show the advantages of TFNN-GRA method.

Research on the Correlation between Industry 4.0 and Sustainable Development in the Machine Tool industry – Application of QFD and Fuzzy MADM methods

<p>Starting in 2025, Taiwan will introduce a requirement that listed companies with a paid-in capital of less than 2 billion NTD need to prepare a sustainability report. Most of the actual income scale of Taiwan’s machine tool industry falls within this range. In response to the requirement, the machine tool industry must reduce its impact on the environment and society and strike a balance while increasing economic returns. This is undoubtedly a major challenge for the machine tool industry, which is one of the most internationally competitive industries in Taiwan. If sustainable development (SD) can be successfully implemented, it will set a benchmark for Taiwan’s traditional industries.</p> <p>The machine tool industry has continued to improve its industrial competitiveness in recent years, especially after Germany proposed the concept of Industry 4.0 in 2013, which accelerated the pace of industrial upgrading and transformation. Studies have shown that the adoption of Industry 4.0 technology can effectively enhance the sustainable performance of enterprises. Additionally, in the literature on SD, it has been confirmed that there is a significant positive relationship between corporate social responsibility and profitability.</p> <p>This study will propose a reasonable and feasible model framework to demonstrate the relationship between SD factors and Industry 4.0 technical indicators, aiming to identify the key Industry 4.0 technologies to improve SD. This study uses the Quality Function Deployment (QFD) method as the basic structure and adopts the Fuzzy Delphi Method (FDM) of the Multiple Attribute Decision Making (MADM), the improved Fuzzy Extended Analytic Hierarchy Process (FEAHP), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for prioritizing performance index factors.</p>

Retracted: Method for Fuzzy Number Intuitionistic Fuzzy Multiple Attribute Decision Making and Its Application to Blended Classroom Teaching Reform Effect Evaluation

Retracted: Method for Fuzzy Number Intuitionistic Fuzzy Multiple Attribute Decision Making and Its Application to Blended Classroom Teaching Reform Effect Evaluation

MADM framework based on the triangular Pythagorean fuzzy sets and applications to college public English teaching quality evaluation

The so-called “college English” teaching quality evaluation is to provide a basic, comprehensive, and realistic evaluation of the relevant aspects and management of teaching implementation on the basis of following the general laws of higher education; It is a comprehensive inspection of “College English” teaching and an important means of quality monitoring and policy adjustment for “College English”. As mentioned earlier, teaching evaluation is a comprehensive evaluation of teaching. Therefore, our evaluation of the quality of university public education is actually an examination of our specific measures in evaluating teaching, teaching methods and methods, teaching literature, and other aspects. The college public English teaching quality evaluation is a classical multiple attribute decision making (MADM). In this paper, we define the triangular Pythagorean fuzzy sets (TPFSs) and investigate the MADM problems under TPFSs. Based on the traditional dual generalized weighted Bonferroni mean (DGWBM) operator and dual generalized weighted geometric Bonferroni mean (DGWGBM) operator, some triangular Pythagorean fuzzy operators are proposed: triangular Pythagorean fuzzy DGWBM (TPFDGWBM) operator and triangular Pythagorean fuzzy DGWGBM (TPFDGWGBM) operator. Accordingly, we have took advantage of these operators to develop some approaches to work out the triangular Pythagorean fuzzy MADM. Ultimately, a practical example for college public English teaching quality evaluation is took advantage of to validate the developed approach, and an influence analysis of the parameter on the final results is been presented to attest its availability and validity.

Triangular Pythagorean fuzzy Bonferroni mean operators in multiple attribute decision making and applications to college English smart classroom teaching quality evaluation

At the stage of college education, English is a very important subject, which is directly related to the enhancement of college students’ English literacy and the improvement of their English level. From the perspective of mobile internet, the construction and application of college English intelligent classroom teaching mode can promote the reform and improvement of traditional English teaching mode. By giving full play to students’ subjectivity, English teaching can be carried out in a modern teaching classroom environment, which is conducive to strengthening students’ comprehensive English ability, which is also very important and meaningful for building an efficient college English classroom. The college English smart classroom (CESC) teaching quality evaluation is a classical multiple attribute decision making (MADM). In this paper, we define the triangular Pythagorean fuzzy set (TPFS) and investigate the multiple attribute decision making problems under it. Accordingly, we take advantage of traditional Bonferroni mean (BM) operator to develop some triangular Pythagorean fuzzy information operators: triangular Pythagorean fuzzy Bonferroni mean (TPFBM) operator and triangular Pythagorean fuzzy weighted Bonferroni mean (TPFWBM) operator. The dominating natures of these operators are researched. Accordingly, the TPFWBM operator is built for triangular Pythagorean fuzzy MADM. Ultimately, a practical example for CESC teaching quality evaluation is took advantage of to validate the developed approach.

Determination of Recipients of Livestock Assistance for Villages Using the Simple Additive Weighting Method

Decision support systems are systems capable of providing data and information. In today's digital and globalization era, where the need for fast, precise and accurate information is very important. What's more, currently various public and private agencies will develop their businesses, one of which is to make changes by utilizing sophisticated technology such as computers as a substitute for human labor, The simple additive weighting method is one of the methods used to solve the problem of fuzzy multiple attribute decision making (FMADM). The simple additive weighting (SAW) method is a method used to find optimal alternatives from a number of alternatives with certain criteria. The result of this research is a software that adopts the SAW method which is able to assist the agriculture and animal husbandry department for decision making in determining recipients of livestock assistance every year.

Decision Support System for Purchasing Speaker Monitor Home Recording Using Fuzzy Multiple Attribute Decision Making

Technological developments in the field of music are currently experiencing progress, including the formation of computer-based recording, namely the Digital Audio Workstation (DAW). Monitor speakers are one of the most important components of a DAW. A good selection of monitor speakers can support the quality of sound produced by a home recording or recording service provider. The many variations and specifications of monitor speakers on the market make it difficult for users to choose based on four criteria: price, response frequency, design criteria, and power output. So it is necessary to make an application that can determine recommendations for purchasing monitor speakers by applying the Fuzzy Multiple Attribute Decision Making Algorithm. The results obtained in this study show that of the five alternative monitor speakers, KRK ROKIT G4 5 has the highest alternative preference rating of 2.2,5 so it can be used as a reference monitor speaker for home recording.

Intuitionistic fuzzy multiple attribute decision making method based on a parametric piecewise score function

The score function and aggregation operator provide the theoretical basis for intuitionistic fuzzy multiple attribute decision making (MADM), where the role of the score function is to compare and rank the intuitionistic fuzzy numbers (IFNs), and the role of the aggregation operator is to integrate the evaluation information. In view of that, this paper proposes a new score function and aggregation operator, and a new intuitionistic fuzzy MADM method. It first constructs a parametric piecewise score function and discusses the influence of hesitancy degree and the parameter λ on it. Moreover, some properties of the constructed score function are discussed, including the monotonicity, maximum, minimum, and range. Then, it introduces a intuitionistic fuzzy modified Einstein aggregation (IFMEWA) operator and proves monotonicity, idempotency and boundedness of IFMEWA operator. Finally, combined with the constructed score function and IFMEWA operator, it proposes a new intuitionistic fuzzy MADM method.

Decision Support System for Determining Homeroom Teachers at SMPN 3 Porsea Using the Simple Additive Weighting Method

Determination of homeroom teachers at SMPN 3 Porsea using the Simple Additive Weighting method. The model used in this decision support system is Fuzzy Multiple Attribute Decision Making (FMADM) which is a system that can produce an alternative decision that can be used as a tool in making decisions. Based on government demands in the field of education to improve the quality of homeroom teachers, system development This decision support is one way to assist in determining the appropriate teacher to be a homeroom teacher. The SAW method was chosen because this method determines the weight value for each attribute, then proceed with a ranking process that will select the best alternative from a number of alternatives in question, namely the teacher who has the highest score based on each predetermined criterion. With this ranking method, the assessment will be more precise because it is based on the criteria and weights that have been determined so as to get accurate results as a decision aid to determine the homeroom teacher at SMPN 3 Porsea.

An innovative fuzzy parameterized MADM approach to site selection for dam construction based on sv-complex neutrosophic hypersoft set

<abstract><p>Dams are water reservoirs that provide adequate freshwater to residential, industrial, and mining sites. They are widely used to generate electricity, control flooding, and irrigate agricultural lands. Due to recent urbanization trends, industrialization, and climatic changes, the construction of dams is in dire need, which is planning intensive, quite expensive, and time-consuming. Moreover, finding an appropriate site to construct dams is also considered a challenging task for decision-makers. The dam site selection problem (DSSP) has already been considered a multi-criteria decision-making (MCDM) problem under uncertain (fuzzy set) environments by several researchers. However, they ignored some essential evaluating features (e.g., (a) fuzzy parameterized grades, which assess the vague nature of parameters and sub-parameters, (b) the hypersoft setting, which provides multi-argument-based domains for the approximation of alternatives, (c) the complex setting which tackles the periodicity of data, and (d) the single-valued neutrosophic setting which facilitates the decision makers to provide their opinions in three-dimensional aspects) that can be used in DSSP to make it more reliable and trustworthy. Thus this study aims to employ a robust fuzzy parameterized algebraic approach which starts with the characterization of a novel structure "fuzzy parameterized single valued complex neutrosophic hypersoft set ($ \tilde{\lambda} $-set)" that is competent to deal with the above-mentioned features jointly. After that, it integrates the concept of fuzzy parameterization, decision-makers opinions in terms of single-valued complex neutrosophic numbers, and the classical matrix theory to compute the score values for evaluating alternatives. Based on the stages of the proposed approach, an algorithm is proposed, which is further explained by an illustrative example in which DSSP is considered a multiple attributes decision-making (MADM) scenario. The computed score values are then used to evaluate some suitable sites (regions) for dam construction. The computational results of the proposed algorithm are found to be precise and consistent through their comparison with some already developed approaches.</p></abstract>

Decision support system in predicting pneumonia transmission in toddlers based on life patterns

The increasingly widespread spread of pneumonia during the Covid-19 pandemic that attacks children, especially toddlers, has caused the under-five mortality rate (IMR) to increase. Pneumonia is the most worrying thing for parents because it is an acute respiratory disease that attacks the lungs due to the lack of special health information for toddlers that parents get about lifestyle during the Covid-19 pandemic. With the health information from the government for toddlers through the media, especially in improving a healthy lifestyle, it is expected to minimize the transmission of pneumonia. The problem that occurs in the transmission of pneumonia among the general public is air pollution by the presence of bacteria, viruses, and fungi or parasites and the most common types of bacteria attack Streptococcus Pneumonia and Haemophilus Influenzae Virus type b (Hib). The weakening of the condition of children with this disease due to lack of adequate oxygen intake so that children will feel pain in the esophagusarea when breathing. To be able to predict the transmission of pneumonia in toddlers based on lifestyle, the Fuzzy Multiple Attribute Decision Making (Fuzzy MADM) method through a Decision Support System (DSS) is used.

SISTEM PENDUKUNG KEPUTUSAN TINDAK PIDANA PADA PENGADILAN NEGERI LUBUK PAKAM MENGGUNAKAN FUZZY MADM

The foundation of the judiciary in Indonesia is a judiciary based on Pancasila which places human dignity in its place and carries out the protection and guarantee of human rights. In making a decision, the judge's decision must always be based on a case delegation letter containing all charges for the defendant's guilt. The judge must be able to process and process the data obtained during the trial process in terms of evidence, witness statements, defense of the defendant, as well as prosecutors' demands, and psychological content. The task of legal judges in determining the decision to be handed down to the defendant is very heavy. Therefore, a system is needed to assist the judges in court, in this case, the judge, so a decision support system is needed to facilitate judges in making decisions based on the facts of the investigation and the facts of the trial. The aim is to assist judges in making decisions on criminal cases of murder that are suspected of being accused. This support system will be applied using the Fuzzy Multiple Attribute Decision Making (FMADM) method using the criteria of Accompanying Allegations, Goods/evidence, mitigating and aggravating things. The results show that the decision support system can help judges, where the system provides recommendations for decisions against the defendant such as the sentence does not need to be reduced, the sentence is reduced and the defendant is released.

Fuzzy Multiple Attribute Decision Making Menggunakan TOPSIS Pada Sistem Pendukung Keputusan Pemilihan Wireless Router

Selection of the right wireless router can maximize the performance of the internet network. Especially for a company whose business is very dependent on the internet network, choosing the right wireless router is an important factor. The purpose of this study is to implement one of the Fuzzy Multiple Attribute Decision Making (FMADM) approaches, namely the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in a decision support system for selecting wireless router devices to help individuals and companies determine the right wireless router and according to what the user wants. The TOPSIS method is used because it is practical in its use, and has simplicity in concept, efficiency in the computational process and the best alternative is obtained by paying attention to the distance of the closest positive ideal solution and the farthest negative ideal solution distance. The system is built with software development techniques using the Extreme Programming (XP) method which begins with the planning, design, coding and testing stages. The developed system has functions such as being able to manage alternative data, criteria data, weight data, alternative values for each criterion, perform calculations using the TOPSIS method and can display the best alternative results. The results of the black-box testing show that the developed system can function and run well. In addition, the results by calculating manually with the system show the same results.

Method for Fuzzy Number Intuitionistic Fuzzy Multiple Attribute Decision Making and Its Application to Blended Classroom Teaching Reform Effect Evaluation

With the continuous development of mobile Internet and educational technology, the deep integration of education and Internet has a great impact on the education concept and teaching mode. The mixed teaching based on Rain Classroom is the specific application of new educational technology in the teaching of Internet plus education. Most of the students in ethnic universities come from the central and western ethnic regions. In addition, the evaluation of blended classroom teaching reform effect is looked as the classical multiple attribute decision making (MADM). We extend the dual MSM (DMSM) operator with fuzzy number intuitionistic fuzzy numbers (FNIFNs) to build the fuzzy number intuitionistic fuzzy dual MSM (FNIFDMSM) operator and fuzzy number intuitionistic fuzzy weighted DMSM (FNIFWDMSM) equation in this study. A few MADM operators are built with FNIFWDMSM operator. Finally, taking blended classroom teaching reform effect evaluation as an useful example, this paper illustrates the depicted approach.