A maximizing dominance degree model based on trust relationships and TODIM method to reach group consensus

2021 ◽  
pp. 1-14
Author(s):  
Yicong Liu ◽  
Junfeng Chu ◽  
Yanyan Wang ◽  
Yingming Wang
Keyword(s):  
Practical Method ◽  
Feedback Mechanism ◽  
Decision Makers ◽  
Group Consensus ◽  
Optimal Model ◽  
Suitable Alternative ◽  
Trust Relationships ◽  
Todim Method ◽  
Consensus Index ◽  
Indirect Trust

To obtain the suitable alternative(s) for the organization, this paper proposes a more practical method to solve the decision-making problems in society. That is combined with the TODIM (TOmada de decisão interativa multicrit e ´ rio). The maximizing dominance degree model to reach consensus is proposed with two following components: (1) constructing the complete trust relationships network; (2) the maximizing dominance degree feedback mechanism to reach group consensus. Therefore, firstly owing to the complexity of the trust relationships network, judging the direct and indirect trust propagation paths among the decision makers (DMs) to construct the complete trust relationships network and identifying the highest value of Trust Score (TS) as the leader is possible. Then identify the inconsistent DM based on the established consensus index. During the feedback process, inconsistent DMs adopt the feedback mechanism based on the dominance degree of the leader until the group consensus is reached. Later, the corresponding ranking result is calculated by the TODIM method. Finally, a numerical example is applied to illustrate the effectiveness and feasibility of the optimal model.

scholarly journals A Hybrid Network Model to Extract Key Criteria and Its Application for Brand Equity Evaluation

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Chin-Yi Chen ◽  
Chung-Wei Li
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Brand Equity ◽  
Program Planning ◽  
Evaluation Criteria ◽  
Practical Method ◽  
Decision Makers ◽  
Hybrid Network ◽  
Proposed Model ◽  
Equity Evaluation

Making a decision implies that there are alternative choices to be considered, and a major challenge of decision-making is to identify the adequate criteria for program planning or problem evaluation. The decision-makers’ criteria consists of the characteristics or requirements each alternative must possess and the alternatives are rated on how well they possess each criterion. We often use criteria developed and used by different researchers and institutions, and these criteria have similar means and can be substituted for one another. Choosing from existing criteria offers a practical method to engineers hoping to derive a set of criteria for evaluating objects or programs. We have developed a hybrid model for extracting evaluation criteria which considers substitutions between the criteria. The model is developed based on Social Network Analysis and Maximum Mean De-Entropy algorithms. In this paper, the introduced methodology will also be applied to analyze the criteria for assessing brand equity as an application example. The proposed model demonstrates that it is useful in planning feasibility criteria and has applications in other evaluation-planning purposes.

Probabilistic uncertain linguistic TODIM method based on the generalized Choquet integral and its application

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xu Xiuqin ◽  
Xie Jialiang ◽  
Yue Na ◽  
Wang Honghui
Keyword(s):  
Design Methodology ◽  
Distance Measure ◽  
Group Decision ◽  
Choquet Integral ◽  
Decision Makers ◽  
Rational Behavior ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Todim Method ◽  
Selection Of

PurposeThe purpose of this paper is to develop a probabilistic uncertain linguistic (PUL) TODIM method based on the generalized Choquet integral, with respect to the interdependencies between criteria, for the selection of the best alternate in the context of multiple criteria group decision-making (MCGDM).Design/methodology/approachOwing to decision makers (DMs) do not always show completely rational and may have the preference of bounded rational behavior, this may affect the result of the MCGDM. At the same time, criteria interaction is a focused issue in MCGDM. Hence, a novel TODIM method based on the generalized Choquet integral selects the best alternate using PUL evaluation, where the generalized Choquet integral is used to calculate the weight of criterion. The generalized PUL distance measure between two probabilistic uncertain linguistic elements (PULEs) is calculated and the perceived dominance degree matrices for each alternate relative to other alternates are obtained. Furthermore, the comprehensive perceived dominance degree of each alternate can be calculated to get the ranking.FindingsPotential application of the PUL-TODIM method is demonstrated through an evaluation example with sensitivity and comparative analysis.Originality/valueAs per author's concern, there are no TODIM methods with probabilistic uncertain linguistic sets (PULTSs) to solve MCGDM problems under uncertainty. Compared with the result of existing methods, the final judgment value of alternates using the extended TODIM methodology is highly corroborated, which proves its potential in solving MCGDM problems under qualitative and quantitative environments.

scholarly journals Consensus-Based Multi-Person Decision Making with Incomplete Fuzzy Preference Relations Using Product Transitivity

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 185 ◽  
Author(s):  
Atiq-ur Rehman ◽  
Mustanser Hussain ◽  
Adeel Farooq ◽  
Muhammad Akram
Keyword(s):  
Decision Making ◽  
Preference Relation ◽  
Selection Procedure ◽  
Feedback Mechanism ◽  
Decision Makers ◽  
Consensus Process ◽  
Preference Relations ◽  
Priority Weights ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

In this paper, a consensus-based method for multi-person decision making (MPDM) using product transitivity with incomplete fuzzy preference relations (IFPRs) is proposed. Additionally, an average aggregation operator has been used at the first level to estimate the missing preference values and construct the complete fuzzy preference relation (FPR). Then it is confirmed to be product consistent by using the transitive closure formula. Following this, weights of decision makers (DMs) are evaluated by merging consistency weights and predefined priority weights (if any). The consistency weights for the DMs are estimated through product consistency investigation of the information provided by each DM. The consensus process determines whether the selection procedure should be initiated or not. The hybrid comprises of a quitting process and feedback mechanism, and is used to enhance the consensus level amongst DMs in case of an inadequate state. The quitting process arises when some DMs decided to leave the course, and is common in MPDM while dealing with a large number of alternatives. The feedback mechanism is the main novelty of the proposed technique which helps the DMs to improve their given preferences based on this consistency. At the end, a numerical example is deliberated to measure the efficiency and applicability of the proposed method after the comparison with some existing models under the same assumptions. The results show that proposed method can offer useful comprehension into the MPDM process.

scholarly journals A Method of Determining Multi-Attribute Weights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 506 ◽  
Author(s):  
Dongsheng Xu ◽  
Yanran Hong ◽  
Kaili Xiang
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Multi Attribute Decision Making ◽  
Weight Method

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.

A two-sided matching method on green suppliers and manufacturers with intuitionistic linguistic preference information

2019 ◽  
Vol 13 ◽  
Author(s):  
Lan-lin Wang ◽  
Zhi Liu ◽  
Yue-ling Zheng ◽  
Feng-juan Gu
Keyword(s):  
Selection Process ◽  
Decision Makers ◽  
Optimal Model ◽  
Matching Method ◽  
Preference Information ◽  
Perceived Values ◽  
Objective Model ◽  
Green Suppliers ◽  
Regret Aversion ◽  
Two Sides

Purpose: Due to the existing methodologies on two-sided matching seldom consider the asymmetry, uncertainty and fuzziness of the preference information, this paper aims to develop a methodology for solving the selection process between green suppliers and manufacturers with intuitionistic linguistic numbers. Methods: This paper first constructs the evaluation indicators for both sides, which are depicted as intuitionistic linguistic numbers. Subsequently, the authors redefine the intuitionistic linguistic numbers’ expected function based on regret theory. By considering the psychological behaviour of the regret aversion of decision makers, the paper constructs the comprehensive perceived values of decision makers. Furthermore, by maximizing the comprehensive perceived values for the two sides, the multi-objectives matching model is established. In addition, this paper adopts a min-max method to transform the multi-objective optimal model into the single-objective model. Conclusions: This paper considers fuzziness and hesitancy of the preference information, and also considering the psychological behaviour of the regret aversion of decision makers, the two-sided matching method proposed by this paper is more validity and effectiveness than existing methods.

scholarly journals AN EXTENDED TODIM METHOD FOR PROJECT MANAGER’S COMPETENCY EVALUATION

2019 ◽  
Vol 25 (7) ◽  
pp. 673-686 ◽  
Author(s):  
Jielin Yin ◽  
Jian Guo ◽  
Tianmeng Ji ◽  
Jingru Cai ◽  
Lei Xiao ◽  
...  
Keyword(s):  
Decision Making ◽  
High Efficiency ◽  
Choquet Integral ◽  
Project Managers ◽  
Project Manager ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Psychological Behavior ◽  
Todim Method ◽  
Competency Evaluation

The project managers’ high efficiency and leadership ability is very important for the success of the whole project. Evaluating the competency of project manager accurately and selecting the suitable project manager from alternatives is a very core research issue that should be paid high attention to in the field of project management. When evaluating the competency of project manager, multiple criteria with interactive relationship should be considered, and the decision makers may have bounded rational behavior which may have a great impact on the result of evaluation, whereas the decision makes’ psychological behavior is rarely taken into account in the existing studies on the evaluation of project managers’ competency. TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) is a multi-criteria decision making method considering the decision makers’ behavior. In this paper, an extended TODIM method which combines λ -fuzzy measure with Choquet integral considering incomplete criteria information and decision makers’ bounded rational behaviors are presented to evaluate the competency of project manager. Furthermore, a numerical example is presented to illustrate the method proposed. We hope that this method can provide some valuable references for the evaluation of project manager’s competency.

scholarly journals An Influence Network-Based Consensus Model for Large-Scale Group Decision Making with Linguistic Information

2022 ◽  
Vol 15 (1) ◽  
Author(s):  
Shengbao Yao ◽  
Miao Gu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Large Scale ◽  
Group Decision ◽  
Decision Makers ◽  
Consensus Model ◽  
Group Consensus ◽  
Preference Information ◽  
Adjustment Strategy ◽  
Consensus Reaching

AbstractThe vast majority of the existing social network-based group decision-making models require extra information such as trust/distrust, influence and so on. However, in practical decision-making process, it is difficult to get additional information apart from opinions of decision makers. For large-scale group decision making (LSGDM) problem in which decision makers articulate their preferences in the form of comparative linguistic expressions, this paper proposes a consensus model based on an influence network which is inferred directly from preference information. First, a modified agglomerative hierarchical clustering algorithm is developed to detect subgroups in LSGDM problem with flexible linguistic information. Meanwhile, a measure method of group consensus level is proposed and the optimal clustering level can be determined. Second, according to the preference information of group members, influence network is constructed by determining intra-cluster and inter-cluster influence relationships. Third, a two-stage feedback mechanism guided by influence network is established for the consensus reaching process, which adopts cluster adjustment strategy and individual adjustment strategy depending on the different levels of group consensus. The proposed mechanism can not only effectively improve the efficiency of consensus reaching of LSGDM, but also take individual preference adjustment into account. Finally, the feasibility and effectiveness of the proposed method are verified by the case of intelligent environmental protection project location decision.

A Weighted Least-Square Dissimilarity Approach for Multiple Criteria ABC Inventory Classification

2018 ◽  
Vol 35 (04) ◽  
pp. 1850025 ◽  
Author(s):  
Sisi Wu ◽  
Yelin Fu ◽  
K. K. Lai ◽  
W. K. John Leung
Keyword(s):  
Classification Problem ◽  
Multiple Criteria ◽  
Least Square ◽  
Decision Makers ◽  
Group Consensus ◽  
Multiple Decision Makers ◽  
Weighted Least Square ◽  
Common Weights ◽  
The Common ◽  
Criteria Importance

The present paper develops a weighted least-square dissimilarity approach to address the Multiple Criteria ABC inventory classification problem, when the different criteria ranking makes impossible to achieve a group consensus. The proposed approach effectively eliminates drawbacks regarding subjective judgements of multiple decision makers on the criteria importance, and comprehensively aggregates all rankings of the criteria importance to provide a more reasonable and effective classification mechanism. The common weights associated with all rankings are determined. An illustrative example is presented to compare the performance of our approach with the existing studies.

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