scholarly journals Single-Valued Neutrosophic Linguistic Logarithmic Weighted Distance Measures and Their Application to Supplier Selection of Fresh Aquatic Products

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 439 ◽  
Author(s):  
Jiefeng Wang ◽  
Shouzhen Zeng ◽  
Chonghui Zhang
Keyword(s):  
Supplier Selection ◽  
Distance Measures ◽  
Aggregation Method ◽  
Weighted Distance ◽  
Aquatic Products ◽  
Multiple Attribute ◽  
Selection For ◽  
Logarithmic Distance ◽  
Magdm Problems ◽  
Selection Of

A single-valued neutrosophic linguistic set (SVNLS) is a popular fuzzy tool for describing deviation information in uncertain complex situations. The aim of this paper is to study some logarithmic distance measures and study their usefulness in multiple attribute group decision making (MAGDM) problems within single-valued neutrosophic linguistic (SVNL) environments. For achieving the purpose, SVNL weighted logarithmic averaging distance (SVNLWLAD) and SVNL ordered weighted logarithmic averaging distance (SVNLOWLAD) measures are firstly developed based on the logarithmic aggregation method. Then, the SVNL combined weighted logarithmic averaging distance (SVNLCWLAD) measure is presented by unifying the advantages of the previous SVNLWLAD and SVNLOWLAD measures. Moreover, a new MAGDM model by utilizing the SVNLCWLAD measure is presented under SVNL environments. Finally, a supplier selection for fresh aquatic products is taken as a case to illustrate the performance of the proposed framework.

scholarly journals GREEN SUPPLER SELECTION BY AN INTEGRATED METHOD WITH STOCHASTIC ACCEPTABILITY ANALYSIS AND MULTIMOORA

2020 ◽  
Vol 26 (3) ◽  
pp. 549-572
Author(s):  
Xiaomei Mi ◽  
Huchang Liao ◽  
Yi Liao ◽  
Qi Lin ◽  
Benjamin Lev ◽  
...  
Keyword(s):  
Supplier Selection ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Uncertain Information ◽  
Integrated Method ◽  
Selection For ◽  
Green Suppliers ◽  
Multimoora Method ◽  
Selection Of

In the process of supplier selection for green supply chain management, uncertain information may appear in alternatives’ performances or experts’ preferences. The stochastic multicriteria acceptability analysis (SMAA) is a beneficial technique to tackling the uncertain information in such a problem and the MULTIMOORA is a robust technique to aggregate alternatives’ utilities. This study dedicates to proposing an SMAA-MULTIMOORA method by considering the advantages of both methods. The integrated method can accept uncertain information as inputs. The steps of the SMAA-MULTIMOORA are illustrated. A case study about the selection of green suppliers is given to show the validity and robustness of the SMAA-MULTIMOORA method.

QUALIFLEX method for MAGDM with probabilistic uncertain linguistic information and its application to green supplier selection

2020 ◽  
Vol 39 (5) ◽  
pp. 6819-6831
Author(s):  
Fan Lei ◽  
Guiwu Wei ◽  
Jiang Wu ◽  
Cun Wei ◽  
Yanfeng Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Linguistic Information ◽  
Suitable Alternative ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Selection Of

Probabilistic uncertain linguistic sets (PULTSs) have extensively been employed in multiple attribute group decision making (MAGDM)problem. The QUALIFLEX method, which is relatively a novel MAGDM technique, aims to obtain the optimal alternative. This paper proposes the probabilistic uncertain linguistic QUALIFLEX (PUL-QUALIFLEX) method with CRITIC method. To show the effectiveness of the designed method, an application is given for green supplier selection and the derived results are compared with some existing methods. Thus, the advantage of this proposed method is that it is simple to understand and easy to compute. The proposed method can also contribute to the selection of suitable alternative successfully in other selection issues.

scholarly journals TOPSIS Method for Probabilistic Linguistic MAGDM with Entropy Weight and Its Application to Supplier Selection of New Agricultural Machinery Products

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 953 ◽  
Author(s):  
Jianping Lu ◽  
Cun Wei ◽  
Jiang Wu ◽  
Guiwu Wei
Keyword(s):  
Supplier Selection ◽  
Scoring Function ◽  
Ideal Solution ◽  
Agricultural Machinery ◽  
Topsis Method ◽  
Entropy Weight ◽  
Suitable Alternative ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Selection Of

In multiple attribute group decision making (MAGDM) problems, uncertain decision information is well-represented by linguistic term sets (LTSs). These LTSs are easily converted into probabilistic linguistic sets (PLTSs). In this paper, a TOPSIS method is proposed for probabilistic linguistic MAGDM in which the attribute weights are completely unknown, and the decision information is in the form of probabilistic linguistic numbers (PLNs). First, the definition of the scoring function is used to solve the probabilistic linguistic entropy, which is then employed to objectively derive the attribute weights. Second, the optimal alternatives are determined by calculating the shortest distance from the probabilistic linguistic positive ideal solution (PLPIS) and on the other side the farthest distance of the probabilistic linguistic negative ideal solution (PLNIS). This proposed method extends the applications range of the traditional entropy-weighted method. Moreover, it doesn’t need the decision-maker to give the attribute weights in advance. Finally, a numerical example for supplier selection of new agricultural machinery products is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate. The proposed method can contribute to the selection of suitable alternative successfully in other selection problems.

2-tuple linguistic Muirhead mean operators for multiple attribute group decision making and its application to supplier selection

Kybernetes ◽  
2016 ◽  
Vol 45 (1) ◽  
pp. 2-29 ◽  
Author(s):  
Jindong Qin ◽  
Xinwang Liu
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Aggregation Operators ◽  
Management Decision ◽  
Linguistic Information ◽  
Content Type ◽  
Multiple Attribute ◽  
Supplier Selection Problem ◽  
Magdm Problems

Purpose – The purpose of this paper is to develop some 2-tuple linguistic aggregation operators based on Muirhead mean (MM), which is combined with multiple attribute group decision making (MAGDM) and applied the proposed MAGDM model for supplier selection under 2-tuple linguistic environment. Design/methodology/approach – The supplier selection problem can be regarded as a typical MAGDM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MAGDM problems with 2-tuple linguistic information based on traditional MM operator. The MM operator is a well-known mean type aggregation operator, which has some particular advantages for aggregating multi-dimension arguments. The prominent characteristic of the MM operator is that it can capture the whole interrelationship among the multi-input arguments. Motivated by this idea, in this paper, the authors develop the 2-tuple linguistic Muirhead mean (2TLMM) operator and the 2-tuple linguistic dual Muirhead mean (2TLDMM) operator for aggregating the 2-tuple linguistic information, respectively. Some desirable properties and special cases are discussed in detail. Based on which, two approaches to deal with MAGDM problems under 2-tuple linguistic information environment are developed. Finally, a numerical example concerns the supplier selection problem is provided to illustrate the effectiveness and feasibility of the proposed methods. Findings – The results show that the proposed can solve the MAGDM problems within the context of 2-tuple linguistic information, in which the attributes are existing interaction phenomenon. Some 2-tuple aggregation operators based on MM have been developed. A case study of supplier selection is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the linguistic decision information in which the attributes are not independent so as to select the most suitable supplier. Practical implications – The proposed methods can solve the 2-tuple linguistic MAGDM problem, in which the interactions exist among the attributes. Therefore, it can be used to supplier selection problems and other similar management decision problems. Originality/value – The paper develop some 2-tuple aggregation operators based on MM, and further present two methods based on the proposed operators for solving MAGDM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

Research on the Methods of Suppliers Selection in the Context of E-Commerce

2010 ◽  
Vol 143-144 ◽  
pp. 509-514
Author(s):  
Shan Lu
Keyword(s):  
Index System ◽  
Supplier Selection ◽  
Empirical Studies ◽  
Aggregation Operators ◽  
Decision Making Process ◽  
The Index System ◽  
Scientific Nature ◽  
Selection For ◽  
Selection Of ◽  
Supplier Credit

The development of e-commerce has had a significant influence on the index system, methods and process of supplier selection for companies. By considering comprehensively the features of supplier selection in the e-commerce environment as well as the traditional index system, the indices for supplier selection can be determined as supplier flexibility, supplier credit, product quality, informatization degree and supply ability.Based on intuitionistic language aggregation operators, the intuitionistic language sets are applied for selecting and evaluating suppliers, and the scientific nature of this decision-making process of selection of suppliers is then verified through empirical studies. It is necessary to further enrich and improve the index system and methods of supplier selection in the future according to features of companies from different industries and with different background.

scholarly journals VIKOR Method for MAGDM Based on Q-Rung Interval-Valued Orthopair Fuzzy Information and Its Application to Supplier Selection of Medical Consumption Products

2020 ◽  
Vol 17 (2) ◽  
pp. 525 ◽  
Author(s):  
Hui Gao ◽  
Linggang Ran ◽  
Guiwu Wei ◽  
Cun Wei ◽  
Jiang Wu
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Intuitionistic Fuzzy Set ◽  
Consumer Products ◽  
Pythagorean Fuzzy Set ◽  
Key Innovation ◽  
Magdm Problems ◽  
Interval Valued ◽  
Selection Of

The VIKOR model has been considered a viable tool for many decision-making applications in the past few years, given the advantages of considering the compromise between maximizing the utility of group and minimizing personal regrets. The q-rung interval-valued orthopair fuzzy set (q-RIVOFS) is a generalization of intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS) and has emerged to solve more complex and uncertain decision making problems which IFS and PFS cannot handle. In this manuscript, the key innovation is to combine the traditional VIKOR model with q-RIVOFS to develop the q-rung interval-valued orthopair fuzzy VIKOR model. In the new developed model, to express more information, the attribute’s values in MAGDM problems are depicted by q-RIVOFNs. First of all, some basic theories and aggregation operators of q-RIVOFNs are simply introduced. Then we develop the origin VIKOR model to q-RIVOFS environment and briefly express the computing steps of this new established model. Thereafter, the effectiveness of the model is verified by an example of supplier selection of medical consumer products and through comparative analysis, the superiority of the new method is further illustrated.

scholarly journals SISTEM PENDUKUNG KEPUTUSAN SELEKSI SUPPLIER BAHAN BAKU DENGAN METODE SIMPLE ADDITIVE WEIGHTING (SAW)

2020 ◽  
Vol 1 (1) ◽  
pp. 24-32
Author(s):  
Oke Hariansyah
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Multiple Attribute Decision Making ◽  
Test Results ◽  
Weighting Method ◽  
Multiple Attribute ◽  
Speed Up ◽  
Simple Additive Weighting ◽  
Industry Needs ◽  
Selection Of

Selection of suppliers for the company or the industry needs to be done to get the supplier truly able to meet the company's needs consistently. In this study, will be appointed a case of finding the best alternative based on the criteria that have been determined using the Fuzzy Multiple Attribute Decision Making (FMADM) Simple Additive Weighting method (SAW). This method was chosen because it is able to select the best alternative from a number of alternatives, in this case the alternative is intended to determine the best supplier based on specified criteria. Based on test results, the application of the system to be implemented to help the work of doing the selection of purchasing parts supplier, can speed up the process of selecting suppliers, and can facilitate the purchasing section chief part in determining the proper supplier selection, proper and appropriate

scholarly journals TOPSIS and Modified TOPSIS: A Comparative Analysis

2021 ◽  
Author(s):  
Subrata Chakraborty
Keyword(s):  
Multiple Attribute Decision Making ◽  
Similar Degree ◽  
Ideal Solution ◽  
Extensive Simulation ◽  
Multiple Attribute ◽  
Simulation Based ◽  
Order Preference ◽  
Modified Topsis ◽  
Selection For ◽  
Selection Of

Selection of an appropriate Multiple Attribute Decision Making (MADM) method for providing a solution to a given MADM problem is always challenging endeavour. The challenge is even greater for situations where for a specific MADM problem there exist multiple MADM methods with similar degree of suitability. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and its dominant variant the Modified TOPSIS methods are two very similar methods applicable to the same type of MADM problems. This study provides extensive simulation-based comparisons and mathematical analysis of these two popular methods in order to clarify the confusion regarding their selection for solving MADM problems.

scholarly journals Entropy-Based GLDS Method for Social Capital Selection of a PPP Project with q-Rung Orthopair Fuzzy Information

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 414
Author(s):  
Li Liu ◽  
Jiang Wu ◽  
Guiwu Wei ◽  
Cun Wei ◽  
Jie Wang ◽  
...  
Keyword(s):  
Social Capital ◽  
Group Decision ◽  
Fuzzy Entropy ◽  
Fuzzy Information ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
The Social ◽  
Dominance Score ◽  
Magdm Problems ◽  
Selection Of

The social capital selection of a public–private-partnership (PPP) project could be regarded as a classical multiple attribute group decision-making (MAGDM) issue. In this paper, based on the traditional gained and lost dominance score (GLDS) method, the q-rung orthopair fuzzy entropy-based GLDS method was used to solve MAGDM problems. First, some basic theories related to the q-rung orthopair fuzzy sets (q-ROFSs) are briefly reviewed. Then, to fuse the q-rung orthopair fuzzy information effectively, the q-rung orthopair fuzzy Hamacher weighting average (q-ROFHWA) operator and q-rung orthopair fuzzy Hamacher weighting geometric (q-ROFHWG) operator based on the Hamacher operation laws are proposed. Moreover, to determine the attribute weights, the q-rung orthopair fuzzy entropy (q-ROFE) is proposed and some significant merits of it are discussed. Next, based on the q-ROFHWA operator, q-ROFE, and the traditional GLDS method, a MAGDM model with q-rung orthopair fuzzy information is built. In the end, a numerical example for social capital selection of PPP projects is provided to testify the proposed method and deliver a comparative analysis.

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