A new fuzzy multiple attributive group decision making methodology and its application to propulsion/manoeuvring system selection problem

2005 ◽  
Vol 166 (1) ◽  
pp. 93-114 ◽  
Author(s):  
A.İ. Ölçer ◽  
A.Y. Odabaşi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Selection Problem ◽  
System Selection

scholarly journals Refractured Well Selection for Multicriteria Group Decision Making by Integrating Fuzzy AHP with Fuzzy TOPSIS Based on Interval-Typed Fuzzy Numbers

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Tiejun Li ◽  
Jianhua Jin ◽  
Chunquan Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Fuzzy Topsis ◽  
Selection Problem ◽  
Triangular Fuzzy Numbers ◽  
Analytic Hierarchy ◽  
Multicriteria Group Decision Making

Multicriteria group decision making (MCGDM) research has rapidly been developed and become a hot topic for solving complex decision problems. Because of incomplete or non-obtainable information, the refractured well-selection problem often exists in complex and vague conditions that the relative importance of the criteria and the impacts of the alternatives on these criteria are difficult to determine precisely. This paper presents a new model for MCGDM by integrating fuzzy analytic hierarchy process (AHP) with fuzzy TOPSIS based on interval-typed fuzzy numbers, to help group decision makers for well-selection during refracturing treatment. The fuzzy AHP is used to analyze the structure of the selection problem and to determine weights of the criteria with triangular fuzzy numbers, and fuzzy TOPSIS with interval-typed triangular fuzzy numbers is proposed to determine final ranking for all the alternatives. Furthermore, the algorithm allows finding the best alternatives. The feasibility of the proposed methodology is also demonstrated by the application of refractured well-selection problem and the method will provide a more effective decision-making tool for MCGDM problems.

scholarly journals FUCOM-MARCOS based Group Decision-making using Dombi Power Aggregation of Dual Probabilistic Linguistic Information

2021 ◽  
Author(s):  
Abhijit Saha ◽  
Arunodaya Raj Mishra ◽  
Pratibha Rani
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Average Operator ◽  
Sensitivity Assessment ◽  
Probabilistic Linguistic Term Sets ◽  
The Stability ◽  
System Selection

Abstract The dual probabilistic linguistic (DPL) term sets are considered superior to probabilistic linguistic term sets. The power average operator can lessen the effects of the extreme assessing data from some decision-makers with prejudice. Further, the Dombi operators are quite flexible with the general parameter during the aggregation process. Moreover, based on deviation from the maximum consistency by the exclusion of the concern of the redundancy of the comparisons made in criteria pairs, FUCOM (full consistency method) is utilized as a subjective criteria weight computing model. Besides, MARCOS (Measurements alternatives and ranking according to compromise solution) method is based on the determination of utility degrees according to the distance from anti-ideal and ideal solutions and their aggregations. In this study, we combine the merits of power average operator, Dombi operator, FUCOM technique and MARCOS for dealing with multi-criteria group decision-making (MCGDM) problems under a DPL setting where rank of the alternatives are obtained through MARCOS method. For aggregating decision-experts preferences, we propose two types of operators, namely- DPL Dombi power weighted averaging and DPL Dombi power weighted geometric aggregation operators. We discuss the elegant properties of these proposed aggregation operators. We provide a case study regarding open source software learning management system selection to focus the practicability and usefulness of the proposed approach. Furthermore, we perform a sensitivity assessment on diverse criteria weight sets in order to test the stability of our developed intriguing approach. To this effect, we also provide a comparison between our approach with various extant methods.

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