The Service Quality Evaluation of Agricultural E-Commerce Based on Interval-Valued Intuitionistic Fuzzy GRA Method

The service quality evaluation of agricultural business-to-customer (B2C) e-commerce is viewed as a multiattribute group decision-making (MAGDM) activity. Thus, a useful MAGDM process is required. Based on the grey relational analysis (GRA) process and the interval-valued intuitionistic fuzzy set (IVIFS), this study defines an interval-valued intuitionistic fuzzy (IVIF) GRA process to depict the service quality of agricultural B2C e-commerce. This is important to agricultural B2C e-commerce because this industry increases rapidly and many new services are innovated. In this article, some necessary definitions related to IVIFSs are reviewed. Additionally, criteria weights are derived using the Criteria Importance Through Intercriteria Correlation method (CRITIC). Subsequently, the GRA method is extended to incorporate IVIFs to obtain a final service alternative. All alternatives can then be ranked, and the best service quality option can be identified and promulgated. Finally, a numerical example and some useful comparative studies are obtained. The analysis results show that the defined algorithm is effective for identifying the service qualities of agricultural B2C e-commerce, which provide a new assessment method for MAGDM.

MBJ-neutrosophic subalgebras and filters in $ BE $-algebras

<abstract><p>The concept of a neutrosophic set, which is a generalization of an intuitionistic fuzzy set and a para consistent set etc., was introduced by F. Smarandache. Since then, it has been studied in various applications. In considering a generalization of the neutrosophic set, Mohseni Takallo et al. used the interval valued fuzzy set as the indeterminate membership function because interval valued fuzzy set is a generalization of a fuzzy set, and introduced the notion of MBJ-neutrosophic sets, and then they applied it to BCK/BCI-algebras. The aim of this paper is to apply the concept of MBJ-neutrosophic sets to a $ BE $-algebra, which is a generalization of a BCK-algebra. The notions of MBJ-neutrosophic subalgebras and MBJ-neutrosophic filters of $ BE $-algebras are introduced and related properties are investigated. The conditions under which the MBJ-neutrosophic set can be a MBJ-neutrosophic subalgebra/filter are searched. Characterizations of MBJ-neutrosophic subalgebras and MBJ-neutrosophic filters are considered. The relationship between an MBJ-neutrosophic subalgebra and an MBJ-neutrosophic filter is established.</p></abstract>

The Intuitionistic Fuzzy FlowSort Method for Multicriteria Group Decision Making

The real life problems are multidimensional in nature and may involve some ambiguity when it comes to decision making. It is, therefore, difficult to design the evaluation criteria precisely and determine the exact value of the attributes in the multicriteria analysis. The intuitionistic fuzzy set (IFS) achieved great success in treating this kind of ambiguity in a great deal of research. The study of sorting problems is an active research issue in the multiple criteria decision aid (MCDA) area. This paper investigated one of the sorting methods, FLOWSORT, and extended it to the multicriteria group decision making based on the output aggregation of the individual sorting results. The rating of each alternative was described through linguistic terms that can be expressed in triangular intuitionistic fuzzy numbers. An illustrative example as well as an empirical comparison with other multi-criteria decision making methods were carried out to validate our extension.

A hybrid risk assessment approach for assessing the earthquake risks in worn-out urban fabrics: a case study in Iran

Purpose To reduce financial and human losses, managing risks associated with earthquakes is essential in practice. However, in using common risk management methods, experts are often faced with ambiguities that can create profound challenges for risk management. Therefore, it is necessary to develop a logical and straightforward risk assessment model to provide scientific and accurate answers to complex problems. This study aims to recommend an innovative combined method based on the probability-impact (P-I) approach and intuitionistic fuzzy set theory to identify and prioritize the essential earthquake risks associated with worn-out urban fabrics in the context of Iran. Design/methodology/approach The opinions of 15 experts in the fields of civil engineering and urban construction were gathered during brainstorming sessions. These brainstorming sessions were conducted to determine the probability of risks and the effect of identified risks. After calculating the severity of risks using the P-I approach and converting them to intuitionistic fuzzy sets, the risks were measured and prioritized based on their individual scores. Findings The study results indicated that risk of damage due to buildings’ age and flooding risk had the highest and lowest priorities in causes of financial damage, respectively. Furthermore, the risk of damage due to building quality (demolition) and building age was the most important. The risk of flooding and damage to communication networks has the lowest importance among causes of fatalities in worn-out urban fabrics. Originality/value The study findings and recommendations can be served as a policy and consultative instrument for the relevant stakeholders in the area of urban management.

Multi-Attribute Decision-Support System Based on Aggregations of Interval-Valued Complex Neutrosophic Hypersoft Set

Hypersoft set is an emerging field of study that is meant to address the insufficiency and the limitation of existing soft-set-like models regarding the consideration and the entitlement of multi-argument approximate function. This type of function maps the multi-subparametric tuples to the power set of the universe. It focuses on the partitioning of each attribute into its attribute-valued set that is missing in existing soft-set-like structures. This study aims to introduce novel concepts of complex intuitionistic fuzzy set and complex neutrosophic set under the hypersoft set environment with interval-valued settings. Two novel structures, that is, interval-valued complex intuitionistic hypersoft set (IV-CIFHS-set) and interval-valued complex neutrosophic hypersoft set (IV-CNHS-set), are developed via employing theoretic, axiomatic, graphical, and algorithmic approaches. After conceptual characterization of essential elementary notions of these structures, decision-support systems are presented with the proposal of algorithms to assist the decision-making process. The proposed algorithms are validated with the help of real-world applications. A comprehensive inter-cum-intra comparison of proposed structures is discussed with the existing relevant models, and their generalization is elaborated under certain evaluating features.

A study on a new method for solving interval neutrosophic linear programming problems

Neutrosophic set theory is a generalization of the intuitionistic fuzzy set which can be considered as a powerful tool to express the indeterminacy and inconsistent information that exist commonly in engineering applications and real meaningful science activities. In this paper an interval neutrosophic linear programming (INLP) model will be presented, where its parameters are represented by triangular interval neutrosophic numbers (TINNs) and call it INLP problem. Afterward, by using a ranking function we present a technique to convert the INLP problem into a crisp model and then solve it by standard methods

On Certain Products of Complex Intuitionistic Fuzzy Graphs

A complex intuitionistic fuzzy set (CIFS) can be used to model problems that have both intuitionistic uncertainty and periodicity. A diagram composed of nodes connected by lines and labeled with specific information may be used to depict a wide range of real-life and physical events. Complex intuitionistic fuzzy graphs (CIFGs) are a broader type of diagram that may be used to manipulate data. In this paper, we define the key operations direct, semistrong, strong, and modular products for complex intuitionistic fuzzy graphs and look at some interesting findings. Further, the strong complex intuitionistic fuzzy graph is defined, and several significant findings are developed. Furthermore, we study the behavior of the degree of a vertex in the modular product of two complex intuitionistic fuzzy graphs.

EVALUATION OF THE ROOT CAUSE OF FAILURE IN A CRAWLER CRANE MACHINE USING HYBRID MCDM MODEL

A real-life case study has been presented in this paper, where a crawler crane machine is investigated for the root cause of failure, using an expert opinion-based technique which comprises of an integrated model which is based on an Intuitionistic Fuzzy TOPSIS model Exponential related function, and the intuitionistic entropy model. The main contribution and advantages of the proposed approach are in the use of a subjective and objective model for the computation of the criteria weight, which allows for complete assessment of the actual performance and value of each of the criteria. The application of the exponential-related function, which represent the aggregated effect of the positive and negative evaluations in the performance ratings of the alternatives based on the intuitionistic fuzzy set (IFS) data used. And finally, the method ranks all alternatives using the exponential-related function matrix, which accounts for the expert's attitudinal character, which a strong influencing factor in subjective assessments like the one used in some of the root cause of failure/reliability analysis.

A New Entropy Measurement for the Analysis of Uncertain Data in MCDA Problems Using Intuitionistic Fuzzy Sets and COPRAS Method

In this paper, we propose a new intuitionistic entropy measurement for multi-criteria decision-making (MCDM) problems. The entropy of an intuitionistic fuzzy set (IFS) measures uncertainty related to the data modelling as IFS. The entropy of fuzzy sets is widely used in decision support methods, where dealing with uncertain data grows in importance. The Complex Proportional Assessment (COPRAS) method identifies the preferences and ranking of decisional variants. It also allows for a more comprehensive analysis of complex decision-making problems, where many opposite criteria are observed. This approach allows us to minimize cost and maximize profit in the finally chosen decision (alternative). This paper presents a new entropy measurement for fuzzy intuitionistic sets and an application example using the IFS COPRAS method. The new entropy method was used in the decision-making process to calculate the objective weights. In addition, other entropy methods determining objective weights were also compared with the proposed approach. The presented results allow us to conclude that the new entropy measure can be applied to decision problems in uncertain data environments since the proposed entropy measure is stable and unambiguous.