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.

An Interactive Signed Distance Approach for Multiple Criteria Group Decision-Making Based on Simple Additive Weighting Method with Incomplete Preference Information Defined by Interval Type-2 Fuzzy Sets

2014 ◽  
Vol 13 (05) ◽  
pp. 979-1012 ◽  
Author(s):  
Ting-Yu Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Information ◽  
Incomplete Preference ◽  
Signed Distance ◽  
Decision Making Problem ◽  
Simple Additive Weighting ◽  
Interval Type

Interval type-2 fuzzy sets (T2FSs) with interval membership grades are suitable for dealing with imprecision or uncertainties in many real-world problems. In the Interval type-2 fuzzy context, the aim of this paper is to develop an interactive signed distance-based simple additive weighting (SAW) method for solving multiple criteria group decision-making problems with linguistic ratings and incomplete preference information. This paper first formulates a group decision-making problem with uncertain linguistic variables and their transformation to interval type-2 trapezoidal fuzzy numbers. Concerning the relative importance of multiple decision-makers and group consensus of fuzzy opinions, a procedure using hybrid averages is then employed to construct a collective decision matrix. By an appropriate extension of the classical SAW approach, this paper utilizes the concept of signed distances and establishes an integrated programming model to manage multi-criteria group decisions under the incomplete and inconsistent preference structure. Further, an interactive procedure is established for group decision making. Finally, the feasibility and effectiveness of the proposed methods are illustrated by a collaborative decision-making problem of patient-centered care (PCC).

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 Uncertain Linguistic Aggregation Distance Measures and Their Application to Group Decision Making

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Wei Li ◽  
Shouzhen Zeng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Distance Measures ◽  
University Faculty ◽  
Linguistic Information ◽  
Weighted Distance ◽  
Special Cases ◽  
Decision Making Problem

We introduce a method based on distance measures for group decision making under uncertain linguistic environment. We develop some uncertain linguistic aggregation distance measures called the uncertain linguistic weighted distance (ULWD) measure, the uncertain linguistic ordered weighted distance (ULOWD) measure, and the uncertain linguistic hybrid weighted distance (ULHWD) measure. We study some of their characteristic, and we prove that the ULWD and the ULOWD are special cases of the ULHWD measure. Finally, we develop an application of the ULHWD measure in a group decision making problem concerning the evaluation of university faculty for tenure and promotion with uncertain linguistic information.

scholarly journals A Novel Approach to Fuzzy Soft Set-Based Group Decision-Making

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Qinrong Feng ◽  
Xiao Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Comparison Analysis ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Novel Approach ◽  
Decision Making Problem ◽  
Fuzzy Soft Sets ◽  
Effective Group

There are many uncertain problems in practical life which need decision-making with soft sets and fuzzy soft sets. The purpose of this paper is to develop an approach to effectively solve the group decision-making problem based on fuzzy soft sets. Firstly, we present an adjustable approach to solve the decision-making problems based on fuzzy soft sets. Then, we introduce knowledge measure and divergence degree based on α-similarity relation to determine the experts’ weights. Further, we develop an effective group decision-making approach with unknown experts’ weights. Finally, sensitivity analysis about the parameters and comparison analysis with other existing methods are given.

A Formal Approach to Handling Conflicts in Multiattribute Group Decision Making

2005 ◽  
Vol 128 (4) ◽  
pp. 678-688 ◽  
Author(s):  
Tung-King See ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Problems ◽  
Team Leaders ◽  
Formal Approach ◽  
Aggregation Functions ◽  
Group Members ◽  
Problem Data

Supporting the decision of a group in engineering design is a challenging and complicated problem when issues like consensus and compromise must be taken into account. In this paper, we present the foundations of the group hypothetical equivalents and inequivalents method and two fundamental extensions making it applicable to new classes of group decision problems. The first extension focuses on updating the formulation to place unequal importance on the preferences of the group members. The formulation presented in this paper allows team leaders to emphasize the input from certain group members based on experience or other factors. The second extension focuses on the theoretical implications of using a general class of aggregation functions. Illustration and validation of the developments are presented using a vehicle selection problem. Data from ten engineering design groups are used to demonstrate the application of the method.

scholarly journals Learning While Deciding in Groups

2019 ◽  
Author(s):  
Scott Tindale ◽  
Jeremy R. Winget
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Processes ◽  
Learning Potential ◽  
Group Members ◽  
Actual Learning

Groups are used to make many important societal decisions. Similar to individuals, by paying attention to the information available during the decision processes and the consequences of the decisions, groups can learn from their decisions as well. In addition, group members can learn from each other by exchanging information and being exposed to different perspectives. However, groups make decisions in many different ways and the potential and actual learning that takes place will vary as a function of the manner in which groups reach consensus. This chapter reviews the literature on group decision making with a special emphasis on how and when group decision making leads to learning. We argue that learning is possible in virtually any group decision making environment but freely interacting groups create the greatest potential for learning. We also discuss when and why group may not always take advantage of the learning potential.

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