Abstract
This paper presents a fuzzy approach for ranking discrete alternatives in multi-attribute decision-making under uncertainty. Linguistic variables approximated by fuzzy numbers were applied for facilitating the making of pairwise comparison by the decision maker in determining the alternative performance and attribute importance using fuzzy extent analysis. The resultant fuzzy assessments were aggregated using the simple additive utility method for calculating the fuzzy utility of each alternative across all the attributes. An ideal solution-based procedure was developed for comparing and ranking these fuzzy utilities, leading to the determination of the overall ranking of all the discrete multi-attribute alternatives. An example is provided that shows the proposed approach is effective and efficient in solving the multi-attribute decision making problem under uncertainty, due to the simplicity and comprehensibility of the underlying concept and the efficiency and effectiveness of the computation involved.
Highlights
Multi-attribute decision making problems are often present in real-world settings, in which discrete alternatives must be assessed by the decision maker to determine their overall rankings, with respect to multiple, usually conflicting, attributes under uncertainty [1,2,3,4,5]
This paper presents a fuzzy approach for ranking discrete multi-attribute alternatives in multi-attribute decision-making under uncertainty
To facilitate the making of subjective assessments by the decision maker, linguistic variables approximated by fuzzy numbers were used to express the subjective assessment [6,12]
Summary
Multi-attribute decision making problems are often present in real-world settings, in which discrete alternatives must be assessed by the decision maker to determine their overall rankings, with respect to multiple, usually conflicting, attributes under uncertainty [1,2,3,4,5].
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