A comparative study of multiple-criteria decision-making methods under stochastic inputs

Athanasios Kolios*, Varvara Mytilinou, Estivaliz Lozano-Minguez, Konstantinos Salonitis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

226 Citations (Scopus)
35 Downloads (Pure)

Abstract

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.

Original languageEnglish
Article number566
Number of pages21
JournalEnergies
Volume9
Issue number7
DOIs
Publication statusPublished - 21 Jul 2016

Keywords

  • analytical hierarchy process (AHP)
  • elimination et choix traduisant la realité (ELECTRE)
  • multi-criteria decision methods
  • preference ranking organization method for enrichment evaluation (PROMETHEE)
  • stochastic inputs
  • support structures
  • technique for the order of preference by similarity to the ideal solution (TOPSIS)
  • weighted product method (WPM)
  • weighted sum method (WSM)
  • wind turbine

Fingerprint

Dive into the research topics of 'A comparative study of multiple-criteria decision-making methods under stochastic inputs'. Together they form a unique fingerprint.

Cite this