M-MACBETH

The M-MACBETH software provides tools to facilitate: Complete model structuring; Management of complex problems involving qualitative value scores and weights; Interactive sensitivity and robustness analyses. MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) is an interactive approach that requires only qualitative judgements about differences to help a decision maker or a decision-advising group quantify the relative attractiveness of options. It employs an initial, interactive, questioning procedure that compares two elements at a time, requesting only a qualitative preference judgement. As judgements are entered into the software, it automatically verifies their consistency. A numerical scale is generated that is entirely consistent with all the decision maker ’s judgements. Through a similar process weights are generated for criteria.


References in zbMATH (referenced in 103 articles , 2 standard articles )

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  1. Corrente, S.; Figueira, J. R.; Greco, S.: Pairwise comparison tables within the deck of cards method in multiple criteria decision aiding (2021)
  2. de Almeida, Adiel Teixeira; Frej, Eduarda Asfora; Roselli, Lucia Reis Peixoto: Combining holistic and decomposition paradigms in preference modeling with the flexibility of FITradeoff (2021)
  3. Jiménez, Mariano; Bilbao-Terol, Amelia; Arenas-Parra, Mar: Incorporating preferential weights as a benchmark into a sequential reference point method (2021)
  4. Chakhar, Salem; Ishizaka, Alessio; Thorpe, Andy; Cox, Joe; Nguyen, Thang; Ford, Liz: Calculating the relative importance of condition attributes based on the characteristics of decision rules and attribute reducts: application to crowdfunding (2020)
  5. Liao, Huchang; Mi, Xiaomei; Xu, Zeshui: A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions (2020)
  6. Mayag, Brice; Bouyssou, Denis: Necessary and possible interaction between criteria in a 2-additive Choquet integral model (2020)
  7. Montibeller, Gilberto; Patel, Pratik; del Rio Vilas, Victor J.: A critical analysis of multi-criteria models for the prioritisation of health threats (2020)
  8. Roszkowska, Ewa; Filipowicz-Chomko, Marzena: Measuring sustainable development in the education area using multi-criteria methods: a case study (2020)
  9. Viappiani, Paolo; Boutilier, Craig: On the equivalence of optimal recommendation sets and myopically optimal query sets (2020)
  10. Kułakowski, Konrad; Szybowski, Jacek; Prusak, Anna: Towards quantification of incompleteness in the pairwise comparisons methods (2019)
  11. Trzaskalik, Tadeusz; Sitarz, Sebastian; Dominiak, Cezary: Bipolar method and its modifications (2019)
  12. Fasth, Tobias; Larsson, Aron; Ekenberg, Love; Danielson, Mats: Measuring conflicts using cardinal ranking: an application to decision analytic conflict evaluations (2018)
  13. Gauvin, Charles; Delage, Erick; Gendreau, Michel: A successive linear programming algorithm with non-linear time series for the reservoir management problem (2018)
  14. Ishizaka, Alessio; Siraj, Sajid: Are multi-criteria decision-making tools useful? An experimental comparative study of three methods (2018)
  15. Labreuche, Christophe: An axiomatization of the Choquet integral in the context of multiple criteria decision making without any commensurability assumption (2018)
  16. Labreuche, Christophe; Grabisch, Michel: Using multiple reference levels in multi-criteria decision aid: the generalized-additive independence model and the Choquet integral approaches (2018)
  17. Longaray, André; Ensslin, Leonardo; Ensslin, Sandra; Alves, Glaucia; Dutra, Ademar; Munhoz, Paulo: Using MCDA to evaluate the performance of the logistics process in public hospitals: the case of a Brazilian teaching hospital (2018)
  18. Oliveira, Mónica D.; Lopes, Diana F.; Bana e Costa, Carlos A.: Improving occupational health and safety risk evaluation through decision analysis (2018)
  19. Sobrie, Olivier; Gillis, Nicolas; Mousseau, Vincent; Pirlot, Marc: UTA-poly and UTA-splines: additive value functions with polynomial marginals (2018)
  20. Trdin, Nejc; Bohanec, Marko: Extending the multi-criteria decision making method DEX with numeric attributes, value distributions and relational models (2018)

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Further publications can be found at: http://www.m-macbeth.com/en/references.html