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A review of fuzzy AHP methods for decision-making with subjective judgements
- Source :
- Expert Systems With Applications
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Analytic Hierarchy Process (AHP) is a broadly applied multi-criteria decision-making method to determine the weights of criteria and priorities of alternatives in a structured manner based on pairwise comparison. As subjective judgments during comparison might be imprecise, fuzzy sets have been combined with AHP. This is referred to as fuzzy AHP or FAHP. An increasing amount of papers are published which describe different ways to derive the weights/priorities from a fuzzy comparison matrix, but seldomly set out the relative benefits of each approach so that the choice of the approach seems arbitrary. A review of various fuzzy AHP techniques is required to guide both academic and industrial experts to choose suitable techniques for a specific practical context. This paper reviews the literature published since 2008 where fuzzy AHP is applied to decision-making problems in industry, particularly the various selection problems. The techniques are categorised by the four aspects of developing a fuzzy AHP model: (i) representation of the relative importance for pairwise comparison, (ii) aggregation of fuzzy sets for group decisions and weights/priorities, (iii) defuzzification of a fuzzy set to a crisp value for final comparison, and (iv) consistency measurement of the judgements. These techniques are discussed in terms of their underlying principles, origins, strengths and weakness. Summary tables and specification charts are provided to guide the selection of suitable techniques. Tips for building a fuzzy AHP model are also included and six open questions are posed for future work.
- Subjects :
- 0209 industrial biotechnology
Operations research
Computer science
Fuzzy set
General Engineering
Analytic hierarchy process
Context (language use)
02 engineering and technology
Defuzzification
Fuzzy logic
Computer Science Applications
Set (abstract data type)
020901 industrial engineering & automation
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Pairwise comparison
Representation (mathematics)
Subjects
Details
- ISSN :
- 09574174
- Volume :
- 161
- Database :
- OpenAIRE
- Journal :
- Expert Systems with Applications
- Accession number :
- edsair.doi.dedup.....a23a8a65b86831e8733d8110cfe6c0e9