An Exponential-Related Function for Decision-Making In Engineering and Management
An intuitionistic fuzzy TOPSIS model, which is based on an exponential-related function (IF-TOPSIS) and a fuzzy entropy method, has been proposed in this study. The exponential-related function, which represents the aggregated effect of positive and negative evaluations in the performance ratings of...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/20251/ http://umpir.ump.edu.my/id/eprint/20251/ http://umpir.ump.edu.my/id/eprint/20251/ http://umpir.ump.edu.my/id/eprint/20251/7/An%20Exponential-Related%20Function%20for%20Decision-Making%20In%20Engineering%20and%20Management.pdf |
| Summary: | An intuitionistic fuzzy TOPSIS model, which is based on an exponential-related function (IF-TOPSIS) and a fuzzy entropy method, has been proposed in this study. The exponential-related function, which represents the aggregated effect of positive and negative evaluations in the performance ratings of the alternatives, based on the intuitionistic fuzzy set (IFS) data. Serves, as a computational tool for measuring the separation distance of decision alternatives from the intuitionistic fuzzy positive and negative ideal solution to determine the relative closeness coefficient. The main advantage of this new approach is that (1) it uses a subjective and objective based approach for the computation of the criteria weight and (2) its simplicity both in its concept and computational procedures. The proposed method has successfully been implemented for the evaluation of some engineering designs related problems including the selection of a preferred floppy disk from a group of design alternatives, the selection of the best concept design for a new air-conditions system and finally, the selection of a preferred mouse from a group of alternatives as a reference for a new design. Also, for each of the three case studies, the method has been compared with some similar computational approaches. |
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