An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS

Madi, Elissa; Garibaldi, Jonathan M.; Wagner, Christian

Abstract

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.

Citation

Madi, E., Garibaldi, J. M., & Wagner, C. (2016). An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS.

• Conference Name: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
• End Date: Jul 29, 2016
• Acceptance Date: Feb 3, 2016
• Publication Date: Jul 24, 2016
• Deposit Date: Aug 3, 2017
• Publicly Available Date: Aug 3, 2017
• Peer Reviewed: Peer Reviewed
• Keywords: FTOPSIS, fuzzy TOPSIS, multicriteria decision making, Technique for Order Preference by Similarity to Ideal Solution, fuzzy sets
• Public URL: https://nottingham-repository.worktribe.com/output/799731
• Publisher URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7737950&isnumber=7737658
• Contract Date: Aug 3, 2017