A novel stochastic group decision-making framework with dual hesitant fuzzy soft set for resilient supplier selection

2021 ◽  
pp. 1-19
Author(s):  
Yuanxiang Dong ◽  
Xinglu Deng ◽  
Xinyu Hu ◽  
Weijie Chen
Keyword(s):  
Decision Making ◽  
Supply Chains ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Decision Makers ◽  
Soft Sets ◽  
Flexible Tool ◽  
Attribute Weights ◽  
Psychological Behavior

Suppliers can be regarded as unavoidable sources of external risks in modern supply chains, which may cause disruption of supply chains. A resilient supplier usually has a high adaptive ability to reduce the vulnerability against disruptions and recover from disruption to keep continuity in operations. This paper develops an effective multi-attribute group decision-making (MAGDM) framework for resilient supplier selection. Because of the many uncertainties in resilient supplier selection, the dual hesitant fuzzy soft sets (DHFSSs), a very flexible tool to express uncertain and complex information of decision-makers, is utilized to cope with it. In order to obtain the resilient supplier’s partial order relationship and consider the psychological behavior of decision-makers, this paper proposes the MAGDM framework with DHFSSs based on the TOPSIS method and prospect theory for resilient supplier selection. Furthermore, we consider the consensus level among experts of different backgrounds and experiences and propose a consensus measure method based dual hesitant fuzzy soft numbers (DHFSNs) before selecting a resilient supplier. The expert weights are calculated by the group consensus level between the expert and the group opinions. Meanwhile, we define the entropy of DHFSSs to determine the attribute weights objectively in the decision-making process. Based on this, the proposed method is applied to a practical manufacturing enterprise with an international supply chain for a resilient supplier selection problem. Finally, by performing a sensitivity analysis and a comparative analysis, the results demonstrate the robustness and validity of the proposed method.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

Multi-Attribute Group Decision Making Method for Preference Conflicting with Heterogeneous Information

2018 ◽  
Vol 7 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Kai-Rong Liang
Keyword(s):  
Decision Making ◽  
Objective Function ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Heterogeneous Information ◽  
Multi Objective ◽  
Attribute Weights ◽  
Relative Closeness ◽  
Decision Making Model

The aim of this article is to propose a multi-objective decision-making method for researching and solving multi-attribute heterogeneous group decision-making problems. This is in the case that the characters of the decision information and decision makers' preferences are heterogeneous, and the weight information is incomplete. In this method, the multi-objective decision-making model, which considers the alternatives decision relative closeness and the preference of heterogeneous degree of decision makers in the objective function, is put forward. In addition, this article uses the minimax method to derive the multi-objective decision-making model and obtain the attribute weights and decision makers weights, and then the optimal scheme is established. Finally, an illustrative example shows the effectiveness of the proposed method.

A Multi-Criteria Intuitionistic Fuzzy Group Decision Making Method for Supplier Selection with VIKOR Method

2012 ◽  
pp. 967-983
Author(s):  
Razieh Roostaee ◽  
Mohammad Izadikhah ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Decision Makers ◽  
Uncertain Information ◽  
Vikor Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
The Right

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain, and is typically a multi-criteria group decision problem. In many practical situations, there usually exists incomplete and uncertain information, and the decision makers cannot easily express their judgments on the candidates with exact and crisp values. Therefore, in this paper an extended VIKOR method for group decision making with intuitionistic fuzzy numbers is proposed to solve the supplier selection problem under incomplete and uncertain information environment. In other researches in this area, the weights of each decision makers and in many of them the weights of criteria are pre-determined, but these weights have been calculated in this paper by using the decision matrix of each decision maker. Also, normalized Hamming distance is proposed to calculate the distance between intuitionistic fuzzy numbers. Finally, a numerical example for supplier selection is given to clarify the main results developed in this paper.

scholarly journals A Decision Making Method using Fuzzy Soft Sets

2014 ◽  
Vol 9 (2) ◽  
Author(s):  
Samsiah Abdul Razak ◽  
Daud Mohamad
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Uncertain Data ◽  
Soft Set ◽  
Decision Makers ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Analytic Hierarchy ◽  
Fuzzy Soft Sets

The introduction of soft set theory by Molodstov has gained attention by many as it is useful in dealing with uncertain data. It is advantageous to use due to its parameterization form of data. This concept has been used in solving many decision making problems and has been generalized in various aspects in particular to fuzzy soft set (FSS) theory. In decision making using FSS, the objective is to select an object from a set of objects with respect to a set of choice parameter using fuzzy values. Although FSS theory has been extensively used in many applications, the importance of weight of parameters has not been highlighted and thus is not incorporated in the calculation. As it depends on one’s perception or opinion, the importance of the parameters may differ from one decision maker to another. Besides, existing methods in FSS only consider one or two decision makers to select the alternatives. In reality, group decision making normally involves more than two decision makers. In this paper we present a method for solving group decision making problems that involves more than two decision makers based on fuzzy soft set by taking into consideration the weight of parameters. The method of lambda – max which frequently utilize in fuzzy analytic hierarchy process (FAHP) has been applied to determine the weight of parameters and an algorithm for solving decision making problems is presented. Finally we illustrate the effectiveness of our method with a numerical example.

scholarly journals Humanitarian Rescue Scheme Selection under the Covid-19 Crisis in China: Based on Group Decision-Making Method

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 668
Author(s):  
Xiaotong Deng ◽  
Zhaojun Kong
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Scheme Selection ◽  
Interval Valued

Humanitarian rescue has become an important part of government emergency management in China. In order to select the optimal humanitarian rescue scheme accurately and in a timely manner in an emergency, reduce the harm of disasters to human life and health, and improve the government’s emergency management ability, a multi-attribute emergency group decision-making method is proposed. First, interval-valued intuitionistic fuzzy sets are used to express the preferences of decision-makers, and interval-valued intuitionistic fuzzy entropy is used to calculate attribute weights. Then, based on the technique for order preference by similarity to an ideal solution (TOPSIS) method, the weight of the decision-maker is calculated. Then, the relevant interval intuitionistic fuzzy operators are used to summarize the preferences of decision-makers in group decision-making. Finally, we will use the closeness ranking method to choose the optimal scheme, and the feasibility and practicability of the proposed method are demonstrated by an example. The example shows that the model is more scientific, objective, and comprehensive in solving the problem of multi-attribute group decision-making than the traditional scheme selection, which only depends on the subjective discussion of decision-makers.

scholarly journals Supplier Selection in Sustainable Supply Chains: A Risk-Based Integrated Group Decision-Making Model

2021 ◽  
Author(s):  
Chong Wu ◽  
Haohui Zou ◽  
David Barnes
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Supply Chains ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Supply Risk ◽  
Sustainable Supply Chains ◽  
Intuitionistic Fuzzy ◽  
Decision Making Model

Abstract With the recent emphasis on supply risk management in sustainable supply chains (SSCs), the evaluation and selection of appropriate suppliers are more important than ever. However, most existing research does not take all three sustainability perspectives of supply risk into account simultaneously and they rarely consider the correlation among supply risk factors in risk assessment. Therefore, considering the uncertain information decision-making environment, this research paper proposes a risk-based integrated group decision-making model for sustainable supplier selection (SSS). First, the weights of decision-makers (DMs) are taken as linguistic terms denoted by intuitionistic fuzzy numbers (IFNs). Second, after obtaining the aggregated intuitionistic fuzzy decision-making matrix considering the expert weights, this study uses the entropy weight method to calculate the criteria weights objectively. Then, the improved failure mode and effects analysis (FMEA) is adopted for the risk assessment to exclude high-risk suppliers. Finally, the extended alternative queuing method (AQM) is applied to rank the qualified suppliers in SSCs. This model can not only enable enterprises to reduce supply risk in SSS practices and identify and prevent the failure modes that lead to supply risk, but also reduce the uncertainty of decision-making, in order to make supplier selection more accurate. The feasibility and effectiveness of the proposed model are illustrated through application in a leading Chinese electrical appliance manufacturing company.

A group consensus decision making based sustainable supplier selection method by combing DEMATEL and VIKOR

2021 ◽  
pp. 1-19
Author(s):  
Jian Wu ◽  
Yuting Jin ◽  
Mi Zhou ◽  
Mingshuo Cao ◽  
Yujia Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Critical Role ◽  
Evaluation Criteria ◽  
Decision Makers ◽  
Group Consensus ◽  
Multiple Attribute ◽  
Sustainable Supplier Selection

Sustainable supplier selection (SSS) plays an increasingly critical role in the stability and development of the organization with increasing environmental awareness. This article proposes a linguistic multiple attribute group decision-making method to select the appropriate sustainable supplier by combing Decision Making and Trial Evaluation Laboratory(DEMATEL) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). To do that, a distribution linguistic based DEMATEL technique is developed to deal with the complexity in criteria of SSS. To eliminate the inconsistency among multiple decision-makers providing the preference information of evaluation criteria, a minimum adjusting cost feedback mechanism is utilized to reach group consensus. Therefore, the proposed weights obtaining method can not only deal with the subjectivity of evaluation criterion but also satisfy group decision-makers with different profits and backgrounds. Then, based on the evaluation matrices of supplier performance, it calculates the ranking of alternative suppliers by the VIKOR method. Hence, it can deal with the ambiguity of decision makers’ evaluation and provide the best solution for decision-makers, as a consequence, it makes the final evaluation result more feasible and operable. Finally, the effectiveness and efficiency of this method are verified based on the actual situation of ABC Company. This study proposed a linguistic multiple attribute group decision-making method to select the appropriate sustainable supplier by combing Decision Making and Trial Evaluation Laboratory(DEMATEL) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). What’s more, the proposed method considered the group consensus reaching processes.

scholarly journals Pythagorean 2-Tuple Linguistic Taxonomy Method for Supplier Selection in Medical Instrument Industries

2019 ◽  
Vol 16 (23) ◽  
pp. 4875 ◽  
Author(s):  
He ◽  
Wei ◽  
Lu ◽  
Wei ◽  
Lin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Medical Instrument ◽  
Weighted Average ◽  
Decision Makers ◽  
The Novel ◽  
Fuzzy Information ◽  
Multiple Attribute

Supplier selection in medical instrument industries is a classical multiple attribute group decision making (MAGDM) problem. The Pythagorean 2-tuple linguistic sets (P2TLSs) can reflect uncertain or fuzzy information well and solve the supplier selection in medical instrument industries, and the original Taxonomy is very appropriate for comparing different alternatives with respect to their advantages from studied attributes. In this study, we present an algorithm that combines Pythagorean 2-tuple linguistic numbers (P2TLNs) with the Taxonomy method, where P2TLNs are applied to express the evaluation of decision makers on alternatives. Relying on the Pythagorean 2-tuple linguistic weighted average (P2TLWA) operator or Pythagorean 2-tuple linguistic weighted geometric (P2TLWG) operator to fuse P2TLNs, the new general framework is established for Pythagorean 2-tuple linguistic multiple attribute group decision making (MAGDM) under the classical Taxonomy method. Ultimately, an application case for supplier selection in medical instrument industries is designed to test the novel method’s applicability and practicality and a comparative analysis with three other methods is used to elaborate further.

scholarly journals Algorithm for Neutrosophic Soft Sets in Stochastic Multi-Criteria Group Decision Making Based on Prospect Theory

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1085 ◽  
Author(s):  
Dong ◽  
Hou ◽  
Gong
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Decision Makers ◽  
Aggregation Rule ◽  
Decision Matrix ◽  
Soft Sets

To address issues involving inconsistencies, this paper proposes a stochastic multi-criteria group decision making algorithm based on neutrosophic soft sets, which includes a pair of asymmetric functions: Truth-membership and false-membership, and an indeterminacy-membership function. For integrating an inherent stochastic, the algorithm expresses the weights of decision makers and parameter subjective weights by neutrosophic numbers instead of determinate values. Additionally, the algorithm is guided by the prospect theory, which incorporates psychological expectations of decision makers into decision making. To construct the prospect decision matrix, this research establishes a conflict degree measure of neutrosophic numbers and improves it to accommodate the stochastic multi-criteria group decision making. Moreover, we introduce the weighted average aggregation rule and weighted geometric aggregation rule of neutrosophic soft sets. Later, this study presents an algorithm for neutrosophic soft sets in the stochastic multi-criteria group decision making based on the prospect theory. Finally, we perform an illustrative example and a comparative analysis to prove the effectiveness and feasibility of the proposed algorithm.

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