A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs
By Athanasios Kolios, Varvara Mytilinou, E. Lozano-Mínguez, Konstantinos Salonitis. 2016
252 citations recorded by the source corpus.
This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative.
Subfields: Artificial Intelligence, Control and Systems Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/41c396f312d76dd80da5353fcc81ff40ca263296
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In Artificial Intelligence
In Control and Systems Engineering
In Management Science and Operations Research
Citations in the corpus
- Generalised framework for multi-criteria method selection (2018, methodology): “They can be categorized into those which, when selecting an MCDA method, were based on: benchmarking [1,19,25,26,46,47] , multi-criteria methods (it was recognized that the issue of selecting an MCDA method is a multi-criteria problem) [48] as well as the informal [16,30,49] or formal…”