Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method
TL;DR: An m-polar fuzzy linguistic TOPSIS approach for multi-criteria group decision-making (MCGDM) is developed and used to evaluate the best alternative, to get more authentic and comparable results and to handle the real life problems of having multi- polar information in terms of linguistic variables and values.
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Abstract: The fuzzy linguistic approach provides favorable outputs in several areas, whose description is relatively qualitative. The encouragement for the utilization of sentences or words instead of numbers is that linguistic characterizations or classifications are usually less absolute than algebraic or arithmetical ones. In this research article, we animate the m-polar fuzzy (mF) linguistic approach and elaborate it with real life examples and tabular representation to develop the affluence of linguistic variables based on mF approach. As an extension of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, we develop an m-polar fuzzy linguistic TOPSIS approach for multi-criteria group decision-making (MCGDM). It is used to evaluate the best alternative, to get more authentic and comparable results and to handle the real life problems of having multi-polar information in terms of linguistic variables and values. In this approach decision-makers contribute their estimations in the form of linguistic term sets. To show the efficiency and compatibility of the proposed approach, we compare it with the m-polar fuzzy linguistic ELECTRE-I (Elimination and Choice Translating Reality) approach. Finally, we draw a flow chart of our proposed approach as an algorithm and generate a computer programming code.
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References
Generalizing TOPSIS for fuzzy multiple-criteria group decision-making
Yu-Jie Wang,Hsuan-Shih Lee +1 more
TL;DR: This paper proposes two operators Up and Lo which satisfy the partial ordering relation on fuzzy numbers to the generalization of TOPSIS and suggests that these two operations are employed to find ideal and negative ideal solutions under a fuzzy environment.
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Behzad Ashtiani,Farzad Haghighirad,Ahmad Makui,Golam ali Montazer +3 more
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TL;DR: The interval-valued fuzzy TOPSIS method is presented aiming at solving MCDM problems in which the weights of criteria are unequal, using interval- valued fuzzy sets concepts.
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A Fuzzy TOPSIS Method for Robot Selection
T.-C. Chu,Yi-Jyun Lin +1 more
TL;DR: A fuzzy TOPSIS method for robot selection is proposed, where the ratings of various alternatives versus various subjective criteria and the weights of all criteria are assessed in linguistic terms represented by fuzzy numbers.
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Fuzzy TOPSIS: A General View
TL;DR: A literature review is conducted, different fuzzy models that have been applied to the decision making field are explored, and some applications of fuzzy TOPSIS are presented.
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A method for group decision-making based on determining weights of decision makers using TOPSIS
TL;DR: A new approach for determining weights of DMs in group decision environment based on an extended TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, which defines the positive ideal solution as the average of group decision.
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