An effective way for managing and controlling a large number of inventory items or stock keeping units (SKUs) is the inventory classification. Traditional ABC analysis which based on only a single criterion is commonly used for classification of SKUs. However, we should consider inventory classification as a multi-criteria problem in practice. In this study, a new method of Evaluation based on Distance from Average Solution (EDAS) is introduced for multi-criteria inventory classification (MCIC) problems. In the proposed method, we use positive and negative distances from the average solution for appraising alternatives (SKUs). To represent performance of the proposed method in MCIC problems, we use a common example with 47 SKUs. Comparing the results of the proposed method with some existing methods shows the good performance of it in ABC classification. The proposed method can also be used for multi-criteria decision-making (MCDM) problems. A comparative analysis is also made for showing the validity and stability of the proposed method in MCDM problems. We compare the proposed method with VIKOR, TOPSIS, SAW and COPRAS methods using an example. Seven sets of criteria weights and Spearman's correlation coefficient are used for this analysis. The results show that the proposed method is stable in different weights and well consistent with the other methods.
In this paper, we presented another form of eight similarity measures between PFSs based on the cosine function between PFSs by considering the degree of positive membership, degree of neutral membership, degree of negative membership and degree of refusal membership in PFSs. Then, we applied these weighted cosine function similarity measures between PFSs to strategic decision making. Finally, an illustrative example for selecting the optimal production strategy is given to demonstrate the efficiency of the similarity measures for strategic decision making problem.
The picture fuzzy set is characterized by three functions expressing the degree of membership, the degree of neutral membership and the degree of non-membership. It was proposed as a generalization of an intuitionistic fuzzy set in order to deal with indeterminate and inconsistent information. In this work, we shall present some novel Dice similarity measures of picture fuzzy sets and the generalized Dice similarity measures of picture fuzzy sets and indicate that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based patterns recognition models with picture fuzzy information. Then, we apply the generalized Dice similarity measures between picture fuzzy sets to building material recognition. Finally, an illustrative example is given to demonstrate the efficiency of the similarity measures for building material recognition.
For this article, we shall expand the TODIM model to the MADM with the picture fuzzy numbers (PFNs). Firstly, the concept, comparative method and distance of PFNs are introduced and the traditional TODIM model is presented. Then, the expanded TODIM model is developed to solve MADM problems with PFNs. Finally, a numerical example is given to verify the proposed approach.
Heronian mean (HM) has the characteristic of capturing the correlations of the aggregated arguments and the neutrosophic set can express the incomplete, indeterminate and inconsistent information, in this paper, we applied the Heronian mean to the neutrosophic set, and proposed some Heronian mean operators. Firstly, we presented some operational laws and their properties of single valued neutrosophic numbers (SVNNs), and analyzed the shortcomings of the existing weighted HM operators which have not idempotency, then we propose the improved generalized weighted Heronian mean (IGWHM) operator and improved generalized weighted geometric Heronian mean (IGWGHM) operator based on crisp numbers, and prove that they can satisfy some desirable properties, such as reducibility, idempotency, monotonicity and boundedness Further, we proposed the single valued neutrosophic number improved generalized weighted Heronian mean (NNIGWHM) operator and single valued the neutrosophic number improved generalized weighted geometric Heronian mean (NNIGWGHM) operator, and some desirable properties and special cases of them are discussed. Moreover, with respect to multiple attribute group decision making (MAGDM) problems in which attribute values take the form of SVNNs, the decision making approaches based on the proposed operators are developed. Finally, an application example has been given to show the decision making steps and to discuss the influence of different parameter values on the decision making results.
In order to survive in the present day global competitive environment, it now becomes essential for the manufacturing organizations to take prompt and correct decisions regarding effective use of their scarce resources. Various multi-criteria decision-making (MCDM) methods are now available to help those organizations in choosing the best decisive course of actions. In this paper, the applicability of weighted aggregated sum product assessment (WASPAS) method is explored as an effective MCDM tool while solving eight manufacturing decision making problems, such as selection of cutting fluid, electroplating system, forging condition, arc welding process, industrial robot, milling condition, machinability of materials, and electro-discharge micro-machining process parameters. It is observed that this method has the capability of accurately ranking the alternatives in all the considered selection problems. The effect of the parameter A. on the ranking performance of WASPAS method is also studied.
The aim of this manuscript is to propose a new extension of the MULTIMOORA method adapted for usage with a neutrosophic set. By using single valued neutrosophic sets, the MULTIMOORA method can be more efficient for solving complex problems whose solving requires assessment and prediction, i.e. those problems associated with inaccurate and unreliable data. The suitability of the proposed approach is presented through an example.
In this paper, we extend MM operator and dual MM (DMM) operator to process the interval-valued Pythagorean fuzzy numbers (IVPFNs) and then to solve the MADM problems. Firstly, we develop some interval-valued Pythagorean fuzzy Muirhead mean operators by extending MM and DMM operators to IVPFNs. Then, we prove some properties and discuss some special cases with respect to the parameter vector. Moreover, we present some new methods to deal with MADM problems with the IVPFNs based on the proposed MM and DMM operators. Finally, we verify the validity and reliability of our methods by using an application example for green supplier selections, and analyse the advantages of our methods by comparing it with other existing methods.
In recent years, we know that gravity solitary waves have gradually become the research spots and aroused extensive attention; on the other hand, the fractional calculus have been applied to the biology, optics and other fields, and it also has attracted more and more attention. In the paper, by employing multi-scale analysis and perturbation methods, we derive a new modified Zakharov-Kuznetsov (mZK) equation to describe the propagation features of gravity solitary waves. Furthermore, based on semi-inverse and Agrawal methods, the integer-order mZK equation is converted into the time-fractional mZK equation. In the past, fractional calculus was rarely used in ocean and atmosphere studies. Now, the study on nonlinear fluctuations of the gravity solitary waves is a hot area of research by using fractional calculus. It has potential value for deep understanding of the real ocean-atmosphere. Furthermore, by virtue of the sech-tanh method, the analytical solution of the time-fractional mZK equation is obtained. Next, using the above analytical solution, a numerical solution of the time-fractional mZK equation is given by using radial basis function method. Finally, the effect of time-fractional order on the wave propagation is explained.
Multi-attribute analysis is a useful tool in many economical, managerial, constructional, etc, problems. The accuracy of performance measures in COPRAS (The multi-attribute COmplex PRoportional ASsessment of alternatives) method is usually assumed to he accurate. This method assumes direct and proportional dependence of the Weight and utility degree of investiaged versions on a system of attributes adequately describing the alternatives and on values and weights of the attributes. However. there is usually some uncertainty involved in all multi-attribute model inputs. The objective of this research is to demonstrate flow simulation can be used to reflect fuzzy inputs, which allows more complete interpretation of model results. A case study is used to reflect fuzzy the concept of general contractor choice of on the basis of multiple attributes of efficiency with fuzzy inputs applying CwOPRAS-G method. The research has concluded that the COPRAS-G method is appropriate to use.