A Biobjective Optimization Model for Expert Opinions Aggregation and Its Application in Group Decision Making

2020 ◽  
pp. 1-11
Author(s):  
Chunli Ji ◽  
Xiwen Lu ◽  
Wenjun Zhang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Optimization Model ◽  
Group Decision ◽  
Expert Opinions ◽  
Biobjective Optimization

Expected consistency-based model and multiplicative DEA cross-efficiency for group decision-making with incomplete distribution linguistic preference relations

2021 ◽  
pp. 1-21
Author(s):  
Jinpei Liu ◽  
Longlong Shao ◽  
Ligang Zhou ◽  
Feifei Jin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Optimization Model ◽  
Group Decision ◽  
Preference Relation ◽  
Preference Relations ◽  
Priority Vector ◽  
Linguistic Preference Relation ◽  
Multiplicative Preference Relations ◽  
High Consistency

Faced with complex decision problems, Distribution linguistic preference relation (DLPR) is an effective way for decision-makers (DMs) to express preference information. However, due to the complexity of the decision-making environment, DMs may not be able to provide complete linguistic distribution for all linguistic terms in DLPRs, which results in incomplete DLPRs. Therefore, in order to solve group decision-making (GDM) with incomplete DLPRs, this paper proposes expected consistency-based model and multiplicative DEA cross-efficiency. For a given incomplete DLPRs, we first propose an optimization model to obtain complete DLPR. This optimization model can evaluate the missing linguistic distribution and ensure that the obtained DLPR has a high consistency level. And then, we develop a transformation function that can transform DLPRs into multiplicative preference relations (MPRs). Furthermore, we design an improved multiplicative DEA model to obtain the priority vector of MPR for ranking all alternatives. Finally, a numerical example is provided to show the rationality and applicability of the proposed GDM method.

scholarly journals Business Intelligence System via Group Decision Making

2016 ◽  
Vol 16 (3) ◽  
pp. 219-229 ◽  
Author(s):  
Daniela Borissova ◽  
Ivan Mustakerov ◽  
Dilian Korsemov
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Business Intelligence ◽  
Optimization Model ◽  
Web Application ◽  
Group Decision ◽  
Evaluation Criteria ◽  
Decision Makers ◽  
Intelligence System ◽  
Three Layer Architecture

Abstract In the paper a business intelligence tool based on group decision making is proposed. The group decision making uses a combinatorial optimization modeling technique. It takes into account weighted coefficients for evaluation criteria assigned by decision makers together with their scores for the alternatives in respect of these criteria. The proposed optimization model for group decision making considers also the knowledge level of the group members involved as decision makers. This optimization model is implemented in three-layer architecture of Web application for business intelligence by group decision making. Developed Web application is numerically tested for a representative problem for software choice considering six decision makers, three alternatives and 19 evaluation criteria. The obtained results show the practical applicability and effectiveness of the proposed approach.

SOME ICOWA OPERATORS AND THEIR APPLICATIONS TO GROUP DECISION MAKING WITH INTERVAL FUZZY PREFERENCE RELATIONS

2013 ◽  
Vol 21 (04) ◽  
pp. 579-601 ◽  
Author(s):  
LIGANG ZHOU ◽  
ZHIFU TAO ◽  
HUAYOU CHEN ◽  
JINPEI LIU
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Optimization Model ◽  
Group Decision ◽  
Weighted Averaging ◽  
Preference Relations ◽  
Ordered Weighted Averaging ◽  
Cowa Operator ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

We develop some new cases of the induced continuous ordered weighted averaging (ICOWA) operator and study their desirable properties, which are very suitable to deal with group decision making (GDM) with interval fuzzy preference relations. First, we present the consensus indicator ICOWA (CI-ICOWA) operator which uses the consensus indicator of the interval fuzzy preference as the order inducing variable in the ICOWA operator. Then the concept of compatibility degree (CD) for two interval fuzzy preference relations is defined based on the continuous ordered weighted averaging (COWA) operator and the compatibility degree ICOWA (CD-ICOWA) operator is proposed which uses the CD as the order inducing variable in the ICOWA operator. Next, we investigate some desirable properties of the CD-ICOWA operator. Additionally, we construct an optimization model to obtain the weights of experts by minimizing the compatibility degree in the GDM. Finally, an illustrative numerical example is used to verify the developed approaches.

scholarly journals DETERMINING WEIGHTS OF FUZZY ATTRIBUTES FOR MULTI-ATTRIBUTE DECISION-MAKING PROBLEMS BASED ON CONSENSUS OF EXPERT OPINIONS

2015 ◽  
Vol 21 (5) ◽  
pp. 738-755 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Hannan Amoozad MAHDIRAJI ◽  
Shide Sadat HASHEMI ◽  
Zenonas TURSKIS
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Expert Opinions ◽  
Decision Making Problem ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Group Opinion ◽  
Selection Of

An important objective of a group decision-making problem is to determine the weights of attributes that are given by experts participating in the decision-making process. Since different decision-makers have unequal importance in decision-making, a series of studies focused on finding a set of appropriate weights for experts participating in a decision problem. In this paper, the problem of weight determination among decision-makers is investigated by extending an algorithm taken from the technique for order preference by similarity-to-ideal solution. In this case, a pair of most compromising and least compromising solutions is derived from individual judgments of decision-makers and then, these solutions are applied as the bases for determining the magnitude of individual alignment with the group opinion by using a closeness coefficient approach. Determining the weights of decision-makers, the group decision-making problem is then solved. Application of the proposed method is illustrated by a numerical example for the selection of a maintenance strategy.

scholarly journals Combinatorial Optimization Model for Group Decision-Making

2018 ◽  
Vol 18 (2) ◽  
pp. 65-73 ◽  
Author(s):  
Dilian Korsemov ◽  
Daniela Borissova ◽  
Ivan Mustakerov
Keyword(s):  
Decision Making ◽  
Combinatorial Optimization ◽  
Group Decision Making ◽  
Optimization Model ◽  
Group Decision ◽  
Numerical Application ◽  
Proposed Model ◽  
Decision Making Problem ◽  
Group Members ◽  
Simple Additive Weighting

Abstract In the article a combinatorial optimization model for group decision-making problem is proposed. The described model relies on extended simple additive weighting model. A distinctive feature of the proposed model is consideration of the importance of experts’ opinions by introducing weighted coefficient for each of experts. This allows flexible adjustment of differences in knowledge and experience of the group members responsible to determine most preferable alternative to be achieved. The numerical application is illustrated by an example for software engineering adopted from D. Krapohl. The obtained results show the practical applicability of the proposed combinatorial optimization model for group decision-making.

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