scholarly journals Dry Bulk Carrier Investment Selection through a Dual Group Decision Fusing Mechanism in the Green Supply Chain

2018 ◽  
Vol 10 (12) ◽  
pp. 4528 ◽  
Author(s):  
Shuang Yao ◽  
Donghua Yu ◽  
Yan Song ◽  
Hao Yao ◽  
Yuzhen Hu ◽  
...  
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Group Decision Making ◽  
Group Decision ◽  
Influence Factors ◽  
Fuzzy Topsis ◽  
Dual Group ◽  
Linguistic Variable ◽  
Green Supply Chain ◽  
The Individual

Uncertain linguistic variables and scoring evaluations are two important evaluation mechanisms in the decision making field. Sustainability requirements for ship investment lead to the complexity of influence factors and the decision making process. The uncertain linguistic assessment features a large amount of ambiguity and subjectivity, while the scoring evaluation features high precision and distinct gradations. This paper constructs a criteria system in the green supply chain and proposes a dual group decision fusing mechanism for integrating the linguistic variable and scoring evaluation into a unified evaluation term. A hierarchical cloud of linguistic variable terms is constructed based on scoring via a reverse cloud generator, and then, the ship investment linguistic terms are transformed into prospect values. In addition, the consistency and investment selection performance are measured after aggregating the individual decision matrices for group decision making. The empirical research results on the selection of dry bulk carriers for investment show that dual group decision fusing mechanisms could effectively improve the consistency, decision making efficiency, and accuracy of dry bulk ship investment choices and reduce the cost of feedback adjustment for group decisions. In comparison with the trapezoidal fuzzy and fuzzy TOPSIS methods of group decision making, the proposed method performs better when there are a large number of alternatives.

Schemes Selection of Yarn Tension Detection and Control Based on Fuzzy Multiple Attribute Group Decision Making

2013 ◽  
Vol 694-697 ◽  
pp. 2829-2834
Author(s):  
Yan Li ◽  
Hui Min Li ◽  
Yi Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Yarn Tension ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
The Individual ◽  
Topsis Technique ◽  
And Control

To evaluate the yarn tension detection and control schemes in rapier looms, a fuzzy multiple-attribute group decision making problem is proposed for the schemes selection. Firstly, important degrees of every attributes from each expert are considered. The individual opinions of each expert are integrated with the similarity of the decision group. And the synthesized weights of each expert are calculated. Secondly, with the aggregation of experts opinions, the group attribute-weights matrixes are obtained. Then the fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is used to sequence the alternatives, and the optimal scheme is decided for yarn tension detection and control system, the decision results illustrate the feasibility and effectiveness of the developed method.

scholarly journals Multi-Criteria Group Decision Making for Green Supply Chain Management under Uncertainty

2018 ◽  
Vol 10 (9) ◽  
pp. 3150 ◽  
Author(s):  
Hepu Deng ◽  
Feng Luo ◽  
Santoso Wibowo
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Individual Decision ◽  
Chain Management

This paper presents a multi-criteria group decision making model for effectively evaluating the performance of green supply chain management (GSCM) practices under uncertainty in an organization. The subjective assessments of individual decision makers are appropriately represented with the use of intuitionistic fuzzy numbers for better tackling the uncertainty existent. An algorithm is developed to assist individual decision makers in evaluating the performance of alternative GSCM practices across all the evaluation criteria. An example is presented for demonstrating the applicability of the proposed model in solving similar problems in the real-world setting.

scholarly journals A Novel Multi-Criteria Group Decision-Making Approach Based on Bonferroni and Heronian Mean Operators under Hesitant 2-Tuple Linguistic Environment

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1489
Author(s):  
Shahzad Faizi ◽  
Wojciech Sałabun ◽  
Nisbha Shaheen ◽  
Atiq ur Rehman ◽  
Jarosław Wątróbski
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Geometric Bonferroni Mean ◽  
The Individual ◽  
Heronian Mean

Ambiguous and uncertain facts can be handled using a hesitant 2-tuple linguistic set (H2TLS), an important expansion of the 2-tuple linguistic set. The vagueness and uncertainty of data can be grabbed by using aggregation operators. Therefore, aggregation operators play an important role in computational processes to merge the information provided by decision makers (DMs). Furthermore, the aggregation operator is a potential mechanism for merging multisource data which is synonymous with cooperative preference. The aggregation operators need to be studied and analyzed from various perspectives to represent complex choice situations more readily and capture the diverse experiences of DMs. In this manuscript, we propose some valuable operational laws for H2TLS. These new operational laws work through the individual aggregation of linguistic words and the collection of translation parameters. We introduced a hesitant 2-tuple linguistic weighted average (H2TLWA) operator to solve multi-criteria group decision-making (MCGDM) problems. We also define hesitant 2-tuple linguistic Bonferroni mean (H2TLBM) operator, hesitant 2-tuple linguistic geometric Bonferroni mean (H2TLGBM) operator, hesitant 2-tuple linguistic Heronian mean (H2TLHM) operator, and a hesitant 2-tuple linguistic geometric Heronian mean (H2TLGHM) operator based on the novel operational laws proposed in this paper. We define the aggregation operators for addition, subtraction, multiplication, division, scalar multiplication, power and complement with their respective properties. An application example and comparison analysis were examined to show the usefulness and practicality of the work.

scholarly journals Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

2015 ◽  
Vol 15 (4) ◽  
pp. 863-874 ◽  
Author(s):  
G. Lee ◽  
K. S. Jun ◽  
E.-S. Chung
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Consensus Building ◽  
Vikor Method ◽  
Flood Vulnerability ◽  
Fuzzy Vikor ◽  
Risk Vulnerability

Abstract. This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

ON GROUP DECISION MAKING UNDER LINGUISTIC ASSESSMENTS

1999 ◽  
Vol 07 (04) ◽  
pp. 301-308 ◽  
Author(s):  
CONG CUONG BUI
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Group Decision Making ◽  
Decision Model ◽  
Group Decision ◽  
Weighted Averaging ◽  
Ordered Weighted Averaging ◽  
Choice Processes ◽  
Aggregation Processes ◽  
The Individual

In this paper we consider a fuzzy logic-based model in group decision making, with a focus on the set of all alternatives and on the individual lingustic preference relations. Some choice processes are devoted to the model using consensus measures and linguistic ordered weighted averaging (LOWA) operator. A multiple criteria group decision model in linguistic setting and some aggregation processes are also considered. The model and the new processes allow to incorporate human consistency in decision support systems.

Sign in / Sign up

Export Citation Format

Share Document