Improved Symmetry Measures of Simplified Neutrosophic Sets and Their Decision-Making Method Based on a Sine Entropy Weight Model

Comprehensive evaluation for the sustainable development of fresh agricultural products logistics enterprises based on combination empowerment-TOPSIS method

To solve the problems of environmental pollution and resource waste caused by the rapid development of cold chain logistics of fresh agricultural products and improve the competitiveness of logistics enterprises in the market, a performance evaluation method of cold chain logistics enterprises based on the combined empowerment-TOPSIS was proposed. Firstly, from the five dimensions of cold supply chain capacity, service quality, economic efficiency, informatization degree and development ability, a comprehensive evaluation system of logistics enterprises' sustainable development is constructed, which consists of 16 indicators, such as storage and preservation capacity, distribution accuracy, and equipment input rate. Then, G1 method and entropy weight method are used to calculate the subjective and objective weights of the evaluation indicators, and the combined weights are calculated with the objective of minimizing the deviation of the subjective and objective weighted attributes. Finally, the TOPSIS method is used to calculate the comprehensive evaluation indicators. The results show that the established performance evaluation model can effectively evaluate the performance of fresh agricultural products logistics enterprises and provide theoretical basis for enterprise logistics management.

Application of evidence reasoning algorithm and QUALIFLEX with single-valued neutrosophic set for MCDM

Multi-criteria decision-making methods often include attributes with uncertain nature in practical applications, single-valued neutrosophic set is an important approach to solve above problem. QUALIFLEX method is a traditional decision method that makes decision by comparing different permutations of alternatives. In this paper, QUALIFLEX method is developed to solve the MCDM problem with the element of decision matrix is the single-valued neutrosophic number. Besides, since the defects of the original QUALIFLEX method about fusing information of different attributes, this paper uses Dempster-Shafer theory of evidence to integrate the information about weight and alternatives. Finally, by comparing the result with other MCDM methods, we find that the new method can not only obtain reasonable results, but also explain the decision results by probability theory. This paper not only develops the traditional MCDM method, but also a meaningful attempt to apply AI algorithm in MCDM method.

Renewable energy selection based on a new entropy and dissimilarity measure on an interval-valued neutrosophic set

Energy plays a central part in economic development, yet alongside fossil fuels bring vast environmental impact. In recent years, renewable energy has gradually become a viable source for clean energy to alleviate and decouple with a negative connotation. Different types of renewable energy are not without trade-offs beyond costs and performance. Multiple-criteria decision-making (MCDM) has become one of the most prominent tools in making decisions with multiple conflicting criteria existing in many complex real-world problems. Information obtained for decision making may be ambiguous or uncertain. Neutrosophic is an extension of fuzzy set types with three membership functions: truth membership function, falsity membership function and indeterminacy membership function. It is a useful tool when dealing with uncertainty issues. Entropy measures the uncertainty of information under neutrosophic circumstances which can be used to identify the weights of criteria in MCDM model. Meanwhile, the dissimilarity measure is useful in dealing with the ranking of alternatives in term of distance. This article proposes to build a new entropy and dissimilarity measure as well as to construct a novel MCDM model based on them to improve the inclusiveness of the perspectives for decision making. In this paper, we also give out a case study of using this model through the process of a renewable energy selection scenario in Taiwan performed and assessed.

Evaluation of Provincial Carbon Neutrality Capacity of China Based on Combined Weight and Improved TOPSIS Model

It will be a huge challenge for China to achieve carbon neutrality by 2060. At present, China needs to understand its own carbon neutrality status and then scientifically plan a path to achieve carbon neutrality. In order to evaluate the carbon neutrality capacity of China’s provinces, this paper firstly constructs an evaluation indicator system, which includes 20 indicators at six levels. Then, a combination of subjective and objective weighting methods, as well as an improved technique for order preference by similarity to an ideal solution (TOPSIS) model, are used to calculate evaluation results. On this basis, the reasons for their different carbon neutrality capacities are analyzed. The results show that the use of renewable energy, maintaining ecological environmental quality, and low-carbon technology are important factors affecting China’s carbon neutrality capacity, and according to the evaluation results, China’s provinces are divided into three categories. Finally, corresponding suggestions for speeding up the pace of carbon neutrality are put forward.

New similarity measures for single-valued neutrosophic sets with applications in pattern recognition and medical diagnosis problems

The single-valued neutrosophic set (SVNS) is a well-known model for handling uncertain and indeterminate information. Information measures such as distance measures, similarity measures and entropy measures are very useful tools to be used in many applications such as multi-criteria decision making (MCDM), medical diagnosis, pattern recognition and clustering problems. A lot of such information measures have been proposed for the SVNS model. However, many of these measures have inherent problems that prevent them from producing reasonable or consistent results to the decision makers. In this paper, we propose several new distance and similarity measures for the SVNS model. The proposed measures have been verified and proven to comply with the axiomatic definition of the distance and similarity measure for the SVNS model. A detailed and comprehensive comparative analysis between the proposed similarity measures and other well-known existing similarity measures has been done. Based on the comparison results, it is clearly proven that the proposed similarity measures are able to overcome the shortcomings that are inherent in existing similarity measures. Finally, an extensive set of numerical examples, related to pattern recognition and medical diagnosis, is given to demonstrate the practical applicability of the proposed similarity measures. In all numerical examples, it is proven that the proposed similarity measures are able to produce accurate and reasonable results. To further verify the superiority of the suggested similarity measures, the Spearman’s rank correlation coefficient test is performed on the ranking results that were obtained from the numerical examples, and it was again proven that the proposed similarity measures produced the most consistent ranking results compared to other existing similarity measures.

Grey SWARA-FUCOM Weighting Method for Contractor Selection MCDM Problem: A Case Study of Floating Solar Panel Energy System Installation

Selection of the most appropriate contractor for the installation of solar panels is essential to maximizing the benefit of this renewable, sustainable energy source. Solar energy is one of the 100% renewable energy sources, but implementation may not be very simple and cost-effective. A key phase in the implementation of renewable energy is the evaluation of contractors for the installation of solar panels, which is addressed as a multi-criteria decision-making (MCDM) problem. A new hybrid method is proposed that combines the stepwise weight analysis ratio assessment (SWARA) and full consistent method (FUCOM) weights that are represented as grey numbers used with traditional grey relational analysis (GRA) and evaluation based on distance from average solution (EDAS) methods. The ranking of contractors by both methods is the same, which confirmed the results presented in this research. The use of the grey SWARA-FUCOM weighting method combined with the GRA and EDAS methods increased the decision-makers’ (DMs) confidence in awarding the installation of the solar panel energy system to the top-ranked contractor.

Generalized Distance-Based Entropy and Dimension Root Entropy for Simplified Neutrosophic Sets

In order to quantify the fuzziness in the simplified neutrosophic setting, this paper proposes a generalized distance-based entropy measure and a dimension root entropy measure of simplified neutrosophic sets (NSs) (containing interval-valued and single-valued NSs) and verifies their properties. Then, comparison with the existing relative interval-valued NS entropy measures through a numerical example is carried out to demonstrate the feasibility and rationality of the presented generalized distance-based entropy and dimension root entropy measures of simplified NSs. Lastly, a decision-making example is presented to illustrate their applicability, and then the decision results indicate that the presented entropy measures are effective and reasonable. Hence, this study enriches the simplified neutrosophic entropy theory and measure approaches.

Entropy, Measures of Distance and Similarity of Q-Neutrosophic Soft Sets and Some Applications

The idea of the Q-neutrosophic soft set emerges from the neutrosophic soft set by upgrading the membership functions to a two-dimensional entity which indicate uncertainty, indeterminacy and falsity. Hence, it is able to deal with two-dimensional inconsistent, imprecise, and indeterminate information appearing in real life situations. In this study, the tools that measure the similarity, distance and the degree of fuzziness of Q-neutrosophic soft sets are presented. The definitions of distance, similarity and measures of entropy are introduced. Some formulas for Q-neutrosophic soft entropy were presented. The known Hamming, Euclidean and their normalized distances are generalized to make them well matched with the idea of Q-neutrosophic soft set. The distance measure is subsequently used to define the measure of similarity. Lastly, we expound three applications of the measures of Q-neutrosophic soft sets by applying entropy and the similarity measure to a medical diagnosis and decision making problems.