Multiple Attribute Decision Making Research Articles

Optimization of autonomous vehicle control system reliability on a commercial scale through LIF dombi methodologies.

The resilient framework of Linguistic Intuitionistic Fuzzy Sets (LIFSs) allows for the representation and management of uncertainties related to intuitionistic judgments and linguistic expressions. Recent advances in passive and active safety systems have reduced highway fatalities. Autonomous vehicles can improve safety, efficiency, and mobility by navigating traffic without a driver. One of the primary benefits associated with this technology is that it reduces the number of traffic collisions that result in millions of fatalities and numerous injuries. In this research work, we devise two novel aggregation operators: the linguistic intuitionistic fuzzy Dombi ordered weighted averaging (LIFDOWA) operator and the linguistic intuitionistic fuzzy Dombi ordered weighted geometric (LIFDOWG) operator, and explore their fundamental structural properties. We provide innovative score and accuracy functions for multiple attribute decision-making (MADM) problems within the framework of LIF knowledge. Moreover, we use these techniques to develop a specialized algorithm for MADM issues that addresses the complexities arising from ambiguous data during the selection process. We also demonstrate the effectiveness of our proposed methods by applying them to solve the MADM scenario of selecting an optimal approach to improve the credibility of autonomous vehicle control systems on a commercial scale. In addition, we also compare and evaluate the authenticity and practicability of the newly designed techniques in comparison to existing methodologies.

Enhanced Cross-Entropy Technique for Triangular Fuzzy Neutrosophic Multiple-Attribute Decision-Making and Applications to Quality Evaluation of Urban-Park Environmental Design

The evaluation of urban park environmental design quality is essential for ensuring that parks meet community needs and environmental sustainability. By comprehensively considering indicators such as functionality, aesthetics, sustainability, and user experience, this evaluation helps designers optimize spatial layouts and enhance the efficiency and aesthetic value of parks. Additionally, good environmental design promotes ecological protection, improves the quality of life for residents, and adds more green spaces to the city, making parks an integral part of daily urban life. The evaluation of urban park environmental design quality is framed as a multiple-attribute decision-making (MADM) problem. This study introduces the triangular fuzzy neutrosophic number cross-entropy (TFNN-CE) method, which integrates traditional cross-entropy with triangular fuzzy neutrosophic sets (TFNSs). Subsequently, the TFNN-CE technique for MADM is established. A numerical example illustrating the evaluation of urban park environmental design quality is provided, alongside several comparative analyses to highlight the advantages of the proposed approach. The key contributions of this research are as follows: (1) the TFNN-CE technique is introduced through the integration of cross-entropy and TFNSs; (2) the TFNN-CE technique is formulated to address MADM problems using TFNSs; (3) an empirical application for assessing urban park environmental design quality is presented to validate the proposed methodology; (4) comparative studies are conducted to substantiate the rationality of the TFNN-CE technique.

Aczel-Alsina Aggregation Operators for Pythagorean Fuzzy Linear Diophantine Set and Application to Multiple-Attribute Decision-Making Problem Related to Medical Diagnosis

Aczel-Alsina Aggregation Operators for Pythagorean Fuzzy Linear Diophantine Set and Application to Multiple-Attribute Decision-Making Problem Related to Medical Diagnosis

An enhanced CRADIS decision model for optimizing radioactive waste reduction through transmutations based on Disc Spherical Fuzzy information

Radioactive waste reduction through transmutation techniques is significant for mitigating environmental risks and ensuring long-term safety. It offers a sustainable approach to minimizing the volume of radioactive waste, contributing to both environmental preservation and enhanced nuclear energy sustainability. This paper introduces an extension of aggregation operations to hybrid operators in Disc Spherical Fuzzy Sets (D-SFSs), including D-SFS algebraic hybrid weighted averaging and D-SFS hybrid geometric aggregation operators. These novel operators are tailored for D-SFSs and are supported by rigorous proofs, enhancing their theoretical robustness. Additionally, a Maximum Deviation Method (MDM) is developed in conjunction with a proposed distance measure to assess attribute weights in Multiple Attribute Decision-Making (MADM) problems with Disc Spherical Fuzzy (D-SF) information. The study proposes a new MADM method in the D-SF environment, leveraging the D-SF distance measure and the Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) method. Notably, the paper focuses on extending D-SFs to the CRADIS method, particularly when weight information is entirely unknown. A comprehensive case study on optimizing radioactive waste volume reduction through transmutation technologies is provided. A comparative analysis with existing decision-making methods validates the improved MADM method’s validity and practicality.

Solving MADM Problems based on Matrix Games with a New Defuzzification Method for Triangular Intuitionistic Fuzzy Numbers

Abstract: The paper discusses about a new defuzzification method called the Comprehensive Li-Samuel ranking for Triangular Intuitionistic Fuzzy Numbers (TrIFNs) which is improved from the Li-Samuel ranking method associated with membership function and Li-Samuel ranking method associated with non-membership function. The Comprehensive Li-Samuel ranking for TrIFNs is utilised to derive the weights for the Multiple Attribute Decision Making (MADM) problems under TrIFN. The MADM problem is solved based on two-person zero-sum game which is converted into a pair of LPP by using Comprehensive Li-Samuel ranking. The process of transforming decision matrix into a matrix game and deriving decision maker’s and attribute weights from the matrix game are discussed. Numerical illustration is given to justify the viability and effectiveness of the proposed method and comparisons are made with existing ranking methods. The comparison study reveals that the proposed method provides the best maximum optimal solution for the decision problem than the existing methods

Taxonomy framework for multiple-attribute decision-making with neutrosophic sets: ESP courses teaching effectiveness case

Taxonomy framework for multiple-attribute decision-making with neutrosophic sets: ESP courses teaching effectiveness case

Selection of third-party logistics in supply chain finance under probabilistic complex hesitant fuzzy sets and distance measures

Financial institutions attach great importance to the multiple attribute decision-making (MADM) problems of selecting an effective third-party logistics (3PL) service provider in supply chain finance. A suitable 3PL service provider can not only assist financial institutions in carrying out supply chain finance activity but can also replace financial institutions in supervising the operation of a target financing supply chain, therefore minimizing financial institutions' operating risks. However, there is no sufficient study on the selection of a 3PL service provider. Hence, the objective of this paper is to establish an innovative concept of the “probabilistic complex hesitant fuzzy set” (PCHFS), which is a hybrid structure of the complex hesitant fuzzy set and the probabilistic fuzzy set to manage complex information in real-decision theory. This paper examines the periodicity of probabilistic fuzzy information and extends the range from [0,1] to the unit disc in the complex plane to provide more ability to describe the full meaning of the information in a mathematical model. Based on the internal structure of the set and to find the degree of discrimination between the pairs of PCHFSs, the generalized distance measures and modified generalized distance measures are defined. Several properties and their relationships between them are derived in detail. Also, several cases of the proposed measures are exposed, which reduces them to the existing studies. Furthermore, based on these proposed measures, a multiple-attribute decision-making (MADM) approach is established in an uncertain environment, and several numerical examples are given to examine the feasibility and validity of the explored measures. Finally, the modified and parameterized distance measures based on PCHFSs are verified by comparing them with some existing measures.

Several intuitionistic fuzzy hamy mean operators with complex interval values and their application in assessing the quality of tourism services.

In order to assess the quality of senior tourism services in vacation destinations, we examine complex interval valued intuitionistic Fuzzy Dombi Hamy Mean (CIVIFDHM) operators. These operators successfully manage imprecision and uncertainty in the preferences of senior tourists. However, the Hamy mean (HM) operator can identify the connections between various input data sets and produce excellent outcomes when combining and evaluating information. We illustrate their usefulness and efficacy through a case study, providing a strong instrument for improving service quality for senior citizens and promoting an inclusive and fulfilling travel experience. In this work, we develop the HM operator and Dombi operations with Complex interval valued intuitionistic fuzzy numbers (CIVIFNs). We recommend the CIVIFDHM operator, complex interval valued intuitionistic fuzzy weighted Dombi Hamy mean (CIVIFWDHM), complex interval valued intuitionistic fuzzy dual Dombi Hamy mean (CIVIFDDHM), and complex interval valued intuitionistic fuzzy weighted dual Dombi Hamy mean (CIVIFWDD) operators. Next, multiple attribute decision making (MADM) models are constructed with the help of CIVIFWDHM and CIVIFWDDHM operators. We provided an evaluation of an older tourism operator in a tourist area as an example to show the suggested models.

An assessment of the prominence and total engagement metrics for ranking interdependent attributes in DEMATEL and WINGS

A weight vector is assigned to the attributes in multiple-attribute decision-making to show their relative importance. The interdependencies among the attributes often influence this weight vector. The decision-making trial and evaluation laboratory (DEMATEL) and weighted influence non-linear gauge system (WINGS) are among those methods that consider these interdependencies. These methods require matrix manipulation with several metrics to evaluate interdependencies. This study investigates the potential irregularities within the metrics employed by these two methods for weighing criteria. It examines these metrics and analyzes their sensitivity to the direction and the level of influence among attributes. We provide several numerical examples and mathematical analyses to evaluate their consistency by comparing the expected outcomes with the outcomes of the metrics. Although the metrics are expected to assign higher importance to the more influencing criteria, the total engagement/prominence metric is not sensitive to the direction and level of influence among attributes. We conclude these metrics are inconsistent and can not be used reliably as a composite indicator. In contrast, we show that the total impact factor reflects both the direction and the level of influence and is a reliable choice for this purpose.

Patient Management System Using Fuzzy Multiple Attribute Decision Making Method with SAW at Noura Aesthetic Clinic

This study presents the development and implementation of a Patient Management System (PMS) at Noura Aesthetic Clinic using the Fuzzy Multiple Attribute Decision Making (FMADM) method with Simple Additive Weighting (SAW). The aim is to enhance the decision-making process for patient treatment prioritization and management. The PMS integrates various patient attributes, including medical history, treatment urgency, and resource availability, into a comprehensive decision-making framework. By employing the FMADM method, the system addresses the inherent uncertainties and subjectivities in patient data, ensuring more accurate and reliable prioritization. The SAW technique further refines this process by assigning weighted scores to each attribute, facilitating a straightforward and effective comparison. This combination allows for a balanced assessment of multiple factors, promoting optimal resource allocation and improving overall patient care. The implementation at Noura Aesthetic Clinic demonstrated significant improvements in operational efficiency and patient satisfaction. The system's adaptability to diverse clinical settings and its user-friendly interface make it a valuable tool for healthcare providers. This study underscores the potential of advanced decision-making methodologies in transforming patient management practices, paving the way for more informed and equitable healthcare delivery.

Critical success factors for the adoption of AVs in sustainable urban transportation

Before integrating Autonomous Vehicles (AVs) into transportation systems, it's important to evaluate various aspects to facilitate their adoption. Numerous factors are likely to be crucial in this process. This research investigates the critical success factors influencing the adoption of AVs in sustainable urban transportation through a hybrid fuzzy Multiple-Attribute Decision-Making (MADM) approach. The primary aim is to identify key criteria and sub-criteria perceived by transport experts, shedding light on the complex dynamics of AV adoption. Methodologically, a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) is employed to unveil cause-and-effect relationships among the main criteria, determining their respective weights. Subsequently, fuzzy Analytic Network Process (ANP) is applied to calculate the weights of criteria and sub-criteria based on the fuzzy DEMATEL results. The study considers seven major factor dimensions: economic, technical, operational, environmental, safety and risk, social and regulatory, and user acceptance. Key findings underscore user acceptance, financial costs, and environmental impact as the most pivotal criteria, emphasising their significance in the eyes of transportation experts. Contrarily, technological and operational criteria hold the lowest weight in the considered criteria for AV adoption in transportation networks. This research provides valuable insights into critical barriers and opportunities in the adoption of AVs, contributing to the advancement of sustainable urban transportation.

Optimizing bioremediation techniques for soil decontamination in a linguistic intuitionistic fuzzy framework

Bioremediation techniques, which harness the metabolic activities of microorganisms, offer sustainable and environmentally friendly approaches to contaminated soil remediation. These methods involve the introduction of specialized microbial consortiums to facilitate the degradation of pollutants, contribute to soil restoration, and mitigate environmental hazards. When selecting the most effective bioremediation technique for soil decontamination, precise and dependable decision-making methods are critical. This research endeavors to tackle the aforementioned concern by utilizing the tool of aggregation operators in the framework of the Linguistic Intuitionistic Fuzzy (LIF) environment. Linguistic Intuitionistic Fuzzy Sets (LIFSs) provide a robust framework for representing and managing uncertainties associated with linguistic expressions and intuitionistic assessments. Aggregation operators enrich the decision-making process by efficiently handling the intrinsic uncertainties, preferences, and priorities of MADM problems; as a consequence, the decisions produced are more reliable and precise. In this research, we utilize this concept to devise innovative aggregation operators, namely the linguistic intuitionistic fuzzy Dombi weighted averaging operator (LIFDWA) and the linguistic intuitionistic fuzzy Dombi weighted geometric operator (LIFDWG). We also demonstrate the critical structural properties of these operators. Additionally, we formulate novel score and accuracy functions for multiple attribute decision-making (MADM) problems within LIF knowledge. Furthermore, we develop an algorithm to confront the complexities associated with ambiguous data in solving decision-making problems in the LIF Dombi aggregation environment. To underscore the efficacy and superiority of our proposed methodologies, we adeptly apply these techniques to address the MADM problem concerning the optimal selection of a bioremediation technique for soil decontamination. Moreover, we present a comparative evaluation to delineate the authenticity and practical applicability of the recently introduced approaches relative to previously formulated techniques.

MEREC-MABAC method based on cumulative prospect theory for picture fuzzy sets: Applications to wearable health technology devices

Since there is a causal connection between the performance of the alternative with criteria removed and the assessment of the criteria weights, Method based on the Removal Effects of Criteria (MEREC) can reflect the objectivity of statistical data from this new perspective. Multi-Attributive Border Approximation area Comparison (MABAC) approach considers the subjective psychological characteristics of decision makers (DMs), particularly personal preferences and cognitive limitations, through expert scoring. Cumulative prospect theory (CPT) takes into account both potential gains and losses. We propose applying the MEREC method to picture fuzzy sets (PFS) for the first time to determine criteria weights. We suggest an alternate ranking approach for the CPT-MABAC algorithm based on the Hamming distance of the picture rejection membership degree that corresponds to four behavioral states: acceptance, opposition, abstention, and rejection. We develop the PFS-MEREC-CPT-MABAC evaluation framework to tackle the multiple attribute decision-making (MADM) problems while evaluating the performance of wearable health technology devices (WHTDs). The model achieves a compromise between objectivity and subjectivity as well as capturing the psychological behavior of the experts. Finally, in order to determine the soundness and effectiveness of this integrated research approach, sensitivity and comparison analysis are done to compare the results of its operation with those of existing models.

An extended power geometric technique for multiple-attribute decision-making under single-valued neutrosophic sets and applications to embedded computers’ performance evaluation

An extended power geometric technique for multiple-attribute decision-making under single-valued neutrosophic sets and applications to embedded computers’ performance evaluation

Multiple attribute decision making based on score function of q-connection numbers, q-CNPWG aggregation operator of q-connection numbers, and set pair analysis theory in the environments of q-rung orthopair fuzzy numbers

This paper proposes a new multiple attribute decision making (MADM) method in the environments of q-rung orthopair fuzzy numbers (q-ROFNs) based on the proposed score function of q-connection numbers (q-CNs), the proposed q-connection number power weighted geometric (q-CNPWG) aggregation operator (AO) of q-CNs, and the set pair analysis (SPA) theory. Firstly, we propose a score function of q-CNs based on the SPA theory, where we also present some properties of the proposed score function of q-CNs. Then, we propose the q-CNPWG AO for aggregating q-CNs, where we also present some properties of the proposed q-CNPWG AO of q-CNs. Finally, we propose a new MADM method in the environments of q-ROFNs based on the proposed score function of q-CNs, the proposed q-CNPWG AO of q-CNs, and the SPA theory. The proposed MADM method can overcome the drawbacks of existing MADM methods in the environments of q-ROFNs, where they cannot distinguish preference orders of alternatives in some situations. The proposed MADM method is very useful for MADM in the environments of q-ROFNs.

Intelligent multiple-attributes decision support for classroom teaching quality evaluation in dance aesthetic education based on the GRA and information entropy

Abstract Dance education in colleges and universities is the most important means of inheriting dance skills, cultivating dance talents, and promoting the prosperity and development of dance art. In the new era, the country’s emphasis on “aesthetic education” has provided fertile policy soil for the development of dance majors in universities. Based on the spiritual and cultural needs of the people and the development needs of the national dance art, it is of great urgency for colleges and universities to explore the future oriented Chinese dance higher education and dance creation. Dance education and dance creation are closely linked and interdependent. In the process of Dance education, dance creation inspiration is stimulated. Dance creation and innovation inject new soul into Dance education. College Dance education should combine the two organically to promote the high-quality development of Chinese dance art. The classroom teaching quality evaluation in dance aesthetic education is classical multiple-attributes decision-making (MADM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the classroom teaching quality evaluation in dance aesthetic education. In this paper, we extend the classical grey relational analysis (GRA) method to the probabilistic hesitancy fuzzy MADM with unknown weight information. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are introduced. Then, the information entropy is used to compute the attribute weights based on the expected values and deviation degree. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MADM under PHFSs. Finally, a practical case study for classroom teaching quality evaluation in dance aesthetic education is designed to validate the proposed method and some comparative studies are also designed to verify the applicability.

CoCoSo framework for multi-attribute decision-making with triangular fuzzy neutrosophic sets: “Innovation and entrepreneurship” evaluation case

The “innovation and Entrepreneurship” education focuses on cultivating students’ “innovation and Entrepreneurship” abilities, reflecting the fundamental requirements of economic progress and social development for the knowledge, ability, and quality structure of talents. Local universities should actively promote the reform of talent cultivation models, establish a scientific “innovation and Entrepreneurship” education target system based on the actual situation of the school, strengthen the construction of “innovation and Entrepreneurship” education courses, build various “innovation and Entrepreneurship” practice platforms, pay attention to the interaction between the first and second classrooms, as well as practical and training platforms, serve the growth and talent development of students, and achieve a comprehensive improvement in the quality of school education, teaching, and talent cultivation. The “innovation and Entrepreneurship” education quality evaluation of local colleges could be considered as multiple attribute decision-making (MADM). Recently, the Combined Compromise Solution (CoCoSo) method and information entropy method was employed to deal with MADM. The triangular fuzzy neutrosophic sets (TFNSs) are employed as a better tool for expressing uncertain information during the “innovation and Entrepreneurship” education quality evaluation of local colleges. In this paper, the triangular fuzzy neutrosophic number CoCoSo (TFNN-CoCoSo) based on the TFNN grey rational coefficients (TFNNGRC) from TFNN positive ideal solution (TFNNPIS) is constructed to cope with the MADM under TFNSs. The information entropy method is employed to compute the weight values based on the TFNNGRC from TFNNPIS under TFNSs. Finally, a numerical example of “innovation and Entrepreneurship” education quality evaluation of local colleges is constructed and some decision comparisons are constructed to verify the TFNN-CoCoSo method.

MADM framework based on interval-valued neutrosophic aczel-alsina power average operator and application to translation teaching quality evaluation of college English

The huge demand for translation talents has prompted the universities to focus on improving the quality of translation teaching. As a necessary means to improve the quality of teaching, translation teaching quality evaluation plays a role in guiding, regulating and managing translation teaching, which is an important part of translation teaching. The translation teaching quality evaluation of college English is viewed as the multiple attribute decision making (MADM). The interval-valued neutrosophic sets (IVNSs) are used as an effective tool for characterizing uncertain information during the translation teaching quality evaluation of college English. In this paper, interval-valued neutrosophic number (IVNN) Aczel-Alsina power average (IVNNAAPA) operator is proposed based on the classical Aczel-Alsina operator and power average (PA) operator. Then, IVNNAAPA operator is employed to cope with MADM problem. Finally, the numerical decision example for translation teaching quality evaluation of college English is employed to illustrate the produced method and some comparative models are used to prove the effectiveness of the IVNNAAPA method.

Sustainable locating of petroleum refinery projects

The Petroleum Refinery Industry (PRI) is notorious for its significant contribution to environmental degradation. Operations of refineries in local neighborhoods often lead to adverse impacts on the surrounding community and environment. However, PRI projects also yield positive effects on local, national, and international economies. Mitigating the negative consequences of refinery operations necessitates a scientific and quantitative approach to selecting refinery locations. This process should consider a multitude of parameters and alternatives, encompassing social and environmental resiliency, transportation factors, and product markets throughout the refinery life cycle, in an integrated manner. Quantifying the impact of these parameters on the triple bottom line is essential for informed decision-making.In this study, we employ a previously developed integrated sustainability assessment framework in conjunction with a Multiple Attribute Decision Making (MADM) based scenario model to evaluate the impact of various location alternatives on the three pillars of sustainability. Despite the complexities inherent in refinery location decisions and the unpredictability of long-term and short-term parameters, this study's life-cycle approach offers a valuable tool for locating petroleum refineries.

Modeling travel mode choice behavior for planned special events using CPT-based HI-MADM approach

ABSTRACT Planned special events (PSEs) can significantly increase traffic demand, posing greater challenges than daily operations. In response, host cities often invest heavily in transportation upgrades. This study proposes a model integrating cumulative prospect theory (CPT) and multiple-attribute decision-making to understand mode choice behavior of PSE attendees. This integration enables direct extraction of traveler preference information, offering a more suitable description of the decision-making process. The decision matrix considers mode and attribute heterogeneity. The reference point for CPT is derived from previous PSE trips or commutes. Furthermore, this paper assesses asymmetric nonlinear sensitivity and distorted perceptions of different attributes. Analysis of mode-choice behavior for PSE participation, using survey data from Tianjin, China, validates the approach. It better characterizes PSE choice behaviors and demonstrates varying sensitivity to gains and losses, dependent on different attributes and distances. Thus, event planners should prioritize improving travel time and convenience to increase public transport mode share.