scholarly journals Emergency Transportation Problem Based on Single-Valued Neutrosophic Set

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Lin Lu ◽  
Xiaochun Luo
Keyword(s):  
Decision Making ◽  
Transport Model ◽  
Scoring Function ◽  
Emergency Operation ◽  
Neutrosophic Set ◽  
Uncertain Information ◽  
Uncertain Environments ◽  
Entropy Weight ◽  
Emergency Transport ◽  
Entropy Weight Method

Emergency events are full of large number of uncertain information. The existence of these uncertain information leads to less research on emergency logistics involving transshipment scenarios. In this paper, a new emergency transport model is proposed, which simulates the scenario of emergency transport from the logistics center to each disaster site and between each disaster site. The single-valued neutrosophic set (SVNS) is applied to transform the emergency transshipment problem into a multiattribute decision-making problem in ambiguous and uncertain environments. Technology for order preference by similarity to ideal solution (TOPSIS) is extended to the single-valued neutrosophic environment to rank and optimize the alternative transshipment routes. Firstly, the attribute weight is determined by using the entropy weight method; secondly, the scoring function of the single-valued neutrosophic fuzzy number is defined; thirdly, the TOPSIS method is used to rank the decision-making; finally, the feasibility and rationality of the proposed method are verified by an emergency operation example.

scholarly journals Multiple Attribute Group Decision Making Based on Simplified Neutrosophic Integrated Weighted Distance Measure and Entropy Method

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Haibo Zhang ◽  
Zhimin Mu ◽  
Shouzhen Zeng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Distance Measure ◽  
Group Decision ◽  
Neutrosophic Set ◽  
Entropy Measure ◽  
Uncertain Information ◽  
Entropy Weight ◽  
Weighted Distance ◽  
Multiple Attribute

Simplified neutrosophic set (SNS) is a popular tool in modelling potential, imprecise, and uncertain information within complex environments. In this paper, a method based on the integrated weighted distance measure and entropy weight is proposed for handling SNS multiple attribute group decision-making (MAGDM) problems. To this end, the simplified neutrosophic (SN) integrated weighted distance (SVNIWD) measure is first developed for overcoming the limitations of the existing methods. Afterward, the proposed SNIWD’s several properties and particular status are studied. Moreover, a flexible and useful MAGDM approach that combines the strengths of the SNIWD and the SNS is proposed, wherein the SN entropy measure is applied to calculate the unknown weight information regarding attributes. Finally, a numerical case of investment evaluation and subsequent comparative analysis are conducted to prove the superiority of the proposed framework.

scholarly journals An Approach toward a Q-Neutrosophic Soft Set and Its Application in Decision Making

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 139 ◽  
Author(s):  
Majdoleen Abu Qamar ◽  
Nasruddin Hassan
Keyword(s):  
Decision Making ◽  
Uncertain Data ◽  
Real Life ◽  
Soft Set ◽  
Neutrosophic Set ◽  
Uncertain Information ◽  
Soft Sets ◽  
Independent Functions ◽  
Axis Of Symmetry ◽  
Set Aggregation

A neutrosophic set was proposed as an approach to study neutral uncertain information. It is characterized through three memberships, T , I and F, such that these independent functions stand for the truth, indeterminate, and false-membership degrees of an object. The neutrosophic set presents a symmetric form since truth enrolment T is symmetric to its opposite false enrolment F with respect to indeterminacy enrolment I that acts as an axis of symmetry. The neutrosophic set was further extended to a Q-neutrosophic soft set, which is a hybrid model that keeps the features of the neutrosophic soft set in dealing with uncertainty, and the features of a Q-fuzzy soft set that handles two-dimensional information. In this study, we discuss some operations of Q-neutrosophic soft sets, such as subset, equality, complement, intersection, union, AND operation, and OR operation. We also define the necessity and possibility operations of a Q-neutrosophic soft set. Several properties and illustrative examples are discussed. Then, we define the Q-neutrosophic-set aggregation operator and use it to develop an algorithm for using a Q-neutrosophic soft set in decision-making issues that have indeterminate and uncertain data, followed by an illustrative real-life example.

scholarly journals Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 877 ◽  
Author(s):  
Yi Cui ◽  
Shangming Jiang ◽  
Juliang Jin ◽  
Ping Feng ◽  
Shaowei Ning
Keyword(s):  
Decision Making ◽  
Water Consumption ◽  
Projection Pursuit ◽  
Crop Water ◽  
Irrigation Scheme ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Projection Pursuit Model ◽  
Grey Relation

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.

scholarly journals A Method of Determining Multi-Attribute Weights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 506 ◽  
Author(s):  
Dongsheng Xu ◽  
Yanran Hong ◽  
Kaili Xiang
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Multi Attribute Decision Making ◽  
Weight Method

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.

scholarly journals Effectiveness of Entropy Weight Method in Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-5 ◽  
Author(s):  
Yuxin Zhu ◽  
Dazuo Tian ◽  
Feng Yan
Keyword(s):  
Decision Making ◽  
Water Source ◽  
Entropy Weight ◽  
Weighting Method ◽  
Numerical Discrimination ◽  
Differentiation Degree ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Degree Of Differentiation ◽  
Index Weight

Entropy weight method (EWM) is a commonly used weighting method that measures value dispersion in decision-making. The greater the degree of dispersion, the greater the degree of differentiation, and more information can be derived. Meanwhile, higher weight should be given to the index, and vice versa. This study shows that the rationality of the EWM in decision-making is questionable. One example is water source site selection, which is generated by Monte Carlo Simulation. First, too many zero values result in the standardization result of the EWM being prone to distortion. Subsequently, this outcome will lead to immense index weight with low actual differentiation degree. Second, in multi-index decision-making involving classification, the classification degree can accurately reflect the information amount of the index. However, the EWM only considers the numerical discrimination degree of the index and ignores rank discrimination. These two shortcomings indicate that the EWM cannot correctly reflect the importance of the index weight, thus resulting in distorted decision-making results.

scholarly journals A Generalized Approach towards Soft Expert Sets via Neutrosophic Cubic Sets with Applications in Games

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 289 ◽  
Author(s):  
Muhammad Gulistan ◽  
Nasruddin Hassan
Keyword(s):  
Decision Making ◽  
Necessary Conditions ◽  
Neutrosophic Set ◽  
Uncertain Information ◽  
Combined Approach ◽  
Soft Sets

Games are considered to be the most attractive and healthy event between nationsand peoples. Soft expert sets are helpful for capturing uncertain and vague information.By contrast, neutrosophic set is a tri-component logic set, thus it can deal with uncertain,indeterminate, and incompatible information where the indeterminacy is quantified explicitly andtruth membership, indeterminacy membership, and falsity membership independent of each other.Subsequently, we develop a combined approach and extend this concept further to introduce thenotion of the neutrosophic cubic soft expert sets (NCSESs) by using the concept of neutrosophiccubic soft sets, which is a powerful tool for handling uncertain information in many problems andespecially in games. Then we define and analyze the properties of internal neutrosophic cubicsoft expert sets (INCSESs) and external neutrosophic cubic soft expert sets (ENCSESs), P-order,P-union, P-intersection, P-AND, P-OR and R-order, R-union, R-intersection, R-AND, and R-OR ofNCSESs. The NCSESs satisfy the laws of commutativity, associativity, De Morgan, distributivity,idempotentency, and absorption. We derive some conditions for P-union and P-intersection of twoINCSESs to be an INCSES. It is shown that P-union and P-intersection of ENCSESs need not be anENCSES. The R-union and R-intersection of the INCSESs (resp., ENCSESs) need not be an INCSES(resp. ENCSES). Necessary conditions for the P-union, R-union and R-intersection of two ENCSESsto be an ENCSES are obtained. We also study the conditions for R-intersection and P-intersectionof two NCSESs to be an INCSES and ENCSES. Finally, for its applications in games, we use thedeveloped procedure to analyze the cricket series between Pakistan and India. It is shown that theproposed method is suitable to be used for decision-making, and as good as or better when comparedto existing models.

scholarly journals New Uncertainty Measure of Rough Fuzzy Sets and Entropy Weight Method for Fuzzy-Target Decision-Making Tables

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Huani Qin ◽  
Darong Luo
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Theoretical Studies ◽  
Uncertainty Measure ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Rough Fuzzy Set ◽  
Fuzzy Target

In the rough fuzzy set theory, the rough degree is used to characterize the uncertainty of a fuzzy set, and the rough entropy of a knowledge is used to depict the roughness of a rough classification. Both of them are effective, but they are not accurate enough. In this paper, we propose a new rough entropy of a rough fuzzy set combining the rough degree with the rough entropy of a knowledge. Theoretical studies and examples show that the new rough entropy of a rough fuzzy set is suitable. As an application, we introduce it into a fuzzy-target decision-making table and establish a new method for evaluating the entropy weight of attributes.

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