scholarly journals A q-rung orthopair fuzzy non-cooperative game method for competitive strategy group decision-making problems based on a hybrid dynamic experts’ weight determining model

2021 ◽  
Author(s):  
Yu-Dou Yang ◽  
Xue-Feng Ding
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Competitive Strategy ◽  
High Efficiency ◽  
Group Decision ◽  
Subjective Evaluation ◽  
Sensitivity Analyses ◽  
Matrix Game ◽  
Strategy Group ◽  
Evaluation Information

AbstractHow to select the optimal strategy to compete with rivals is one of the hottest issues in the multi-attribute decision-making (MADM) field. However, most of MADM methods not only neglect the characteristics of competitors’ behaviors but also just obtain a simple strategy ranking result cannot reflect the feasibility of each strategy. To overcome these drawbacks, a two-person non-cooperative matrix game method based on a hybrid dynamic expert weight determination model is proposed for coping with intricate competitive strategy group decision-making problems within q-rung orthopair fuzzy environment. At the beginning, a novel dynamic expert weight calculation model, considering objective individual and subjective evaluation information simultaneously, is devised by integrating the superiorities of a credibility analysis scale and a Hausdorff distance measure for q-rung orthopair fuzzy sets (q-ROFSs). The expert weights obtained by the above model can vary with subjective evaluation information provided by experts, which are closer to the actual practices. Subsequently, a two-person non-cooperative fuzzy matrix game is formulated to determine the optimal mixed strategies for competitors, which can present the specific feasibility and divergence degree of each competitive strategy and be less impacted by the number of strategies. Finally, an illustrative example, several comparative analyses and sensitivity analyses are conducted to validate the reasonability and effectiveness of the proposed approach. The experimental results demonstrate that the proposed approach as a CSGDM method with high efficiency, low computation complexity and little calculation burden.

scholarly journals A Novel Group Decision-Making Method Based on Generalized Distance Measures of PLTSs on E-Commerce Shopping

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Juxiang Wang ◽  
Jian Yuan ◽  
Jiajing Zhang ◽  
Miao Tang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Distance Measures ◽  
Sensitivity Analyses ◽  
Linguistic Term ◽  
Probabilistic Linguistic Term Sets ◽  
Generalized Distance Measures ◽  
Evaluation Information ◽  
Generalized Distance

In multiattribute group decision-making (MAGDM), due to quantity, fuzziness, and complexity of evaluation linguistic information on commodities, traditional distance measures need to be extended to the integration of evaluation information under a multigranular probabilistic linguistic environment. A more reasonable method is proposed to deal with the missing value in the evaluation information. On the basis of the generalized distance measures and filling in the missing evaluation information, some novel distance measures between two multigranular probabilistic linguistic term sets (PLTSs) are presented in this paper. Based on these distance measures, three extended decision-making (DM) algorithms based on TOPSIS, the extended TOPSIS, and VIKOR are proposed, which are MGPL-TOPSIS, MGPL-ETOPSIS, and MGPL-VIKOR, respectively. The case analyses on purchasing a car are provided to illustrate the application of the extended multiattribute group decision-making (MAGDM) algorithms. Then, sensitivity analyses based on PT are proposed as well. In particular, the extended TOPSIS method is presented. These results demonstrate the novelty, feasibility, and rationality of the distance measures between two multigranular PLTSs proposed in this paper.

Application of Targeted Consistency-Adjusting Method in Group Decision-Making

2014 ◽  
Vol 590 ◽  
pp. 773-777
Author(s):  
Quan Mi Liao ◽  
Chao Wang ◽  
Yu Wang ◽  
Sheng Huang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
High Efficiency ◽  
Group Decision ◽  
Fuzzy Theory ◽  
New Method ◽  
Multiple Attribute ◽  
Longitudinal Position ◽  
Evaluation Information ◽  
Original Information

For multiple attribute group decision-making problems in intuitionistic fuzzy theory, a new targeted consistency-adjusting method is proposed to insure the efficiency and consistency of the decision process as well as preserving the original information of the experts. To reach this goal, the new method modifies the evaluation information of the expert who has large difference with the group evaluation information in the level of attribute which differs from the traditional modification without target. By applying the new method in longitudinal position selection model of engine room in naval ships, the practicality of the method is proved. By contrasting to traditional method, it is indicated that the method adjusts evaluation information with high efficiency and little modification of original information.

Heterogeneous multi-attribute case retrieval method based on group decision making using incomplete weight information

2021 ◽  
pp. 1-13
Author(s):  
Kai Zhang ◽  
Jing Zheng ◽  
Ying-Ming Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Interval Numbers ◽  
Retrieval Method ◽  
Incomplete Weight ◽  
Incomplete Weight Information ◽  
Evaluation Information

Case-based reasoning (CBR) is one of the most popular methods used in emergency decision making (EDM). Case retrieval plays a key role in EDM processes based on CBR and usually functions by retrieving similar historical cases using similarity measurements. Decision makers (DMs), thus, choose the most appropriate historical cases. Although uncertainty and fuzziness are present in the EDM process, in-depth research on these issues is still lacking. In this study, a heterogeneous multi-attribute case retrieval method based on group decision making (GDM) with incomplete weight information is developed. First, the case similarities between historical and target cases are calculated, and a set of similar historical cases is constructed. Six formats of case attributes are considered, namely crisp numbers, interval numbers, linguistic variables, intuitionistic fuzzy numbers, single-valued neutrosophic numbers (NNs) and interval-valued NNs. Next, the evaluation information from the DMs is expressed using single-valued NNs. Additionally, the evaluation utilities of similar historical cases are obtained by aggregating the evaluation information. The comprehensive utilities of similar historical cases are obtained using case similarities and evaluation utilities. In this process, the weights of incomplete information are determined by constructing optimization models. Furthermore, the most appropriate similar historical case is selected according to the comprehensive utilities. Finally, the proposed method is demonstrated using two examples; its performance is then compared with those of other similar methods to demonstrate its validity and efficacy.

scholarly journals A Multi-Criteria Group Decision-Making Method with Possibility Degree and Power Aggregation Operators of Single Trapezoidal Neutrosophic Numbers

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 590 ◽  
Author(s):  
Xiaohui Wu ◽  
Jie Qian ◽  
Juanjuan Peng ◽  
Changchun Xue
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Practical Problem ◽  
Group Decision ◽  
Information Aggregation ◽  
Aggregation Operators ◽  
Previous Approach ◽  
Complex Information ◽  
Evaluation Information

Single valued trapezoidal neutrosophic numbers (SVTNNs) are very useful tools for describing complex information, because of their advantage in describing the information completely, accurately and comprehensively for decision-making problems. In the paper, a method based on SVTNNs is proposed for dealing with multi-criteria group decision-making (MCGDM) problems. Firstly, the new operations SVTNNs are developed for avoiding evaluation information aggregation loss and distortion. Then the possibility degrees and comparison of SVTNNs are proposed from the probability viewpoint for ranking and comparing the single valued trapezoidal neutrosophic information reasonably and accurately. Based on the new operations and possibility degrees of SVTNNs, the single valued trapezoidal neutrosophic power average (SVTNPA) and single valued trapezoidal neutrosophic power geometric (SVTNPG) operators are proposed to aggregate the single valued trapezoidal neutrosophic information. Furthermore, based on the developed aggregation operators, a single valued trapezoidal neutrosophic MCGDM method is developed. Finally, the proposed method is applied to solve the practical problem of the most appropriate green supplier selection and the rank results compared with the previous approach demonstrate the proposed method's effectiveness.

Probability multi-valued neutrosophic ELECTRE method for multi-criteria group decision-making

2020 ◽  
Vol 39 (5) ◽  
pp. 7587-7604
Author(s):  
Li Zhang ◽  
Shufeng Cheng ◽  
Peide Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Distance Measure ◽  
Group Decision ◽  
Neutrosophic Sets ◽  
Logistics Outsourcing ◽  
Outranking Relations ◽  
Electre Method ◽  
Evaluation Information

Probability multi-valued neutrosophic sets (PMVNSs) can better describe the incomplete and indeterminate evaluation information, and the ELECTRE method can rank the alternatives in the light of the outranking relations among criteria. To combine their advantages, this paper introduces an extended ELECTRE method to address multi-criteria group decision-making (MCGDM) problems with the information of PMVNSs. Firstly, we introduce the definitions of PMVNSs and the classical ELECTRE method, discuss the ELECTRE-based outranking relations for PMVNSs and analyze some properties of them. Furthermore, the probability multi-valued neutrosophic ELECTRE method is developed to address MCGDM problems based on the proposed distance measure and outranking relations for PMVNSs. Finally, a typical example for logistics outsourcing provider selection is devoted to demonstrate the feasibility of the proposed approach. Moreover, the same example-based comparisons with other existing methods are carried out, the results show our proposed approach outperforms the existing methods in solving the MCGDM problems with PMVNSs.

Local adjustment strategy-driven probabilistic linguistic group decision-making method and its application for fog-haze influence factors evaluation

2020 ◽  
pp. 1-20
Author(s):  
Lidan Pei ◽  
Feifei Jin ◽  
Reza Langari ◽  
Harish Garg
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Influence Factors ◽  
Adjustment Process ◽  
Preference Relations ◽  
Adjustment Strategy ◽  
Probabilistic Linguistic Term Sets ◽  
Ranking Order ◽  
Evaluation Information

Unlike other linguistic modellings, probabilistic linguistic term sets can express clearly the importance of different linguistic variables. The notion of Probabilistic Linguistic Preference Relations (PLPRs) constitutes an extension of linguistic preference relations, and as such has received increasing attention in recent years. In group decision-making (GDM) problems with PLPRs, the processes of consistency adjustment, consensus-achieving and desirable alternative selection play a key role in deriving the reliable GDM results. Therefore, this paper focuses on the construction of a GDM method for PLPRs with local adjustment strategy. First, we redefine the concepts of multiplicative consistency and consistency index for PLPRs, and some properties for multiplicative consistent PLPRs are studied. Then, in order to obtain the acceptable multiplicative consistent PLPRs, we propose a convergent consistency adjustment algorithm. Subsequently, a consensus-achieving method with PLPRs is constructed for reaching the consensus goal of experts. In both consistency adjustment process and consensus-achieving method, the local adjustment strategy is utilized to retain the original evaluation information of experts as much as possible. Finally, a GDM method with PLPRs is investigated to determine the reliable ranking order of alternatives. In order to show the advantages of the developed GDM method with PLPRs, an illustration for determining the ranking of fog-haze influence factors is given, which is followed by the comparative analysis to clarify its validity and merits.

scholarly journals AN APPROACH TO GROUP DECISION MAKING BASED ON 2-DIMENSION UNCERTAIN LINGUISTIC INFORMATION

2012 ◽  
Vol 18 (3) ◽  
pp. 424-437 ◽  
Author(s):  
Peide Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Multiple Attribute Decision Making ◽  
Maximum Deviation ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Evaluation Information

Based on the definition of 2-dimension linguistic information of multiple attribute decision making problems proposed by Zhu, Zhou and Yang (2009), the information on evaluation is extended to 2-dimension uncertain linguistic variables, and a new method is proposed to solve the multiple-attribute group decision making problems in which the attribute values take the form of 2-dimension uncertain linguistic variables and the attribute weights are unknown. Firstly, the II class of uncertain linguistic information is transformed into the subjective weights of the experts, and then the subjective weights, the similarity degree of experts’ evaluation information and authority weights are aggregated to the comprehensive weights of each expert. By the comprehensive weights, the group decision making matrix is produced by weighting evaluation information of each expert. Then the maximum deviation method is used to calculate the attribute weights and TOPSIS method is proposed to rank the alternatives. Finally, an example is given to illustrate the decision-making steps and the effectiveness of this method.

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