Implementing stochastic multicriteria acceptability analysis
By Tommi Tervonen, Risto Lahdelma. European Journal of Operational Research, 2007
298 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/45634c345ac7253a2f893e8f6d1a4f67cc77e314
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Salvatore Greco
- Alessio Ishizaka
- Gianpiero Torrisi
- Benedetto Matarazzo
- Md Mizanur Rahman
- J. Paatero
- Tommi Tervonen
- Risto Lahdelma
In Management Science and Operations Research
- Salvatore Greco
- Alessio Ishizaka
- Benedetto Matarazzo
- Gianpiero Torrisi
- Md Mizanur Rahman
- J. Paatero
- Tommi Tervonen
- Risto Lahdelma
Citations in the corpus
- Risk-based classification system of nanomaterials (2009, background): “For more information on how these were implemented, see Tervonen and Lahdelma (2007).”
- Stochastic multi-attribute acceptability analysis (SMAA): an application to the ranking of Italian regions (2018, methodology): “…to compute the ranking acceptability indices bkr and, moreover, for the values phk the estimates supplied by the Monte Carlo method are surely acceptable (e.g., Tervonen & Lahdelma, 2007, show that 10,000 extractions are enough to obtain an error limit of 0.01 for bkr with a confidence of 95%).”
- Evaluation of choices for sustainable rural electrification in developing countries: A multicriteria approach (2013, methodology): “SMAA method can even handle alternatives which possess uncertain, inaccurate or missing information (what often happens for rural electrification cases) (Tervonen and Lahdelma, 2007).”