An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS
Decision making is an important process for organizations. Common practice involves evaluation of prioritized alternatives based on a given set of criteria. These criteria conflict with each other and commonly no solution can satisfy all criteria simultaneously. This problem is known as Multi Criter...
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| Format: | Conference or Workshop Item |
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2016
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| Online Access: | https://eprints.nottingham.ac.uk/34646/ |
| _version_ | 1848794902429696000 |
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| author | Madi, Elissa Garibaldi, Jonathan M. Wagner, Christian |
| author_facet | Madi, Elissa Garibaldi, Jonathan M. Wagner, Christian |
| author_sort | Madi, Elissa |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Decision making is an important process for organizations. Common practice involves evaluation of prioritized alternatives based on a given set of criteria. These criteria conflict with each other and commonly no solution can satisfy all criteria simultaneously. This problem is known as Multi Criteria Decision Making (MCDM) or Multi Criteria Decision Analysis (MCDA) problem. One of the well-known techniques in MCDM is the ‘Technique for Order Preference by Similarity to Ideal Solution’ (TOPSIS) which was introduced by Hwang and Yoon in 1981 [1]. However, this technique uses crisp information which is impractical in many real world situations because decision makers usually express opinions in natural language such as Poor and Good. Information in the form of natural language, i.e. words, in turn is characterized by fuzziness and uncertainty (i.e. ‘what is the meaning of poor’). This uncertainty can be a challenge for decision makers. Zadeh [2] introduced the concept of fuzzy sets, which enables systematic reasoning with imprecise and fuzzy information by using fuzzy sets to represent linguistic terms numerically to then handle uncertain human judgement. |
| first_indexed | 2025-11-14T19:23:34Z |
| format | Conference or Workshop Item |
| id | nottingham-34646 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:23:34Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-346462020-05-04T17:59:57Z https://eprints.nottingham.ac.uk/34646/ An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS Madi, Elissa Garibaldi, Jonathan M. Wagner, Christian Decision making is an important process for organizations. Common practice involves evaluation of prioritized alternatives based on a given set of criteria. These criteria conflict with each other and commonly no solution can satisfy all criteria simultaneously. This problem is known as Multi Criteria Decision Making (MCDM) or Multi Criteria Decision Analysis (MCDA) problem. One of the well-known techniques in MCDM is the ‘Technique for Order Preference by Similarity to Ideal Solution’ (TOPSIS) which was introduced by Hwang and Yoon in 1981 [1]. However, this technique uses crisp information which is impractical in many real world situations because decision makers usually express opinions in natural language such as Poor and Good. Information in the form of natural language, i.e. words, in turn is characterized by fuzziness and uncertainty (i.e. ‘what is the meaning of poor’). This uncertainty can be a challenge for decision makers. Zadeh [2] introduced the concept of fuzzy sets, which enables systematic reasoning with imprecise and fuzzy information by using fuzzy sets to represent linguistic terms numerically to then handle uncertain human judgement. 2016-07-24 Conference or Workshop Item PeerReviewed Madi, Elissa, Garibaldi, Jonathan M. and Wagner, Christian (2016) An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS. In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 24-29 Jul 2016, Vancouver, Canada. FTOPSIS fuzzy TOPSIS multicriteria decision making Technique for Order Preference by Similarity to Ideal Solution fuzzy sets http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7737950&isnumber=7737658 |
| spellingShingle | FTOPSIS fuzzy TOPSIS multicriteria decision making Technique for Order Preference by Similarity to Ideal Solution fuzzy sets Madi, Elissa Garibaldi, Jonathan M. Wagner, Christian An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS |
| title | An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS |
| title_full | An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS |
| title_fullStr | An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS |
| title_full_unstemmed | An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS |
| title_short | An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS |
| title_sort | exploration of issues and limitations in current methods of topsis and fuzzy topsis |
| topic | FTOPSIS fuzzy TOPSIS multicriteria decision making Technique for Order Preference by Similarity to Ideal Solution fuzzy sets |
| url | https://eprints.nottingham.ac.uk/34646/ https://eprints.nottingham.ac.uk/34646/ |