Modeling uncertainty in multi-criteria decision analysis

By Ian N. Durbach, T. Stewart. European Journal of Operational Research, 2012

366 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a1b1b915a8c2ac68c8d2a96afdda76e01caedb54

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

1. Piotr L. Jankowski
2. Holger R. Maier
3. Bakhtiar Feizizadeh
4. Thomas Blaschke
5. Graeme C. Dandy
6. Kwok-Wing Chau

In Management Science and Operations Research

1. Marjolijn Haasnoot
2. Jan H. Kwakkel
3. Piotr L. Jankowski
4. Bakhtiar Feizizadeh
5. P. Thokala
6. Thomas Blaschke

In Statistics and Probability

1. Piotr L. Jankowski
2. Holger R. Maier
3. Jan H. Kwakkel
4. Maarten J. IJzerman
5. Bakhtiar Feizizadeh
6. Marjolijn Haasnoot
7. Joseph H. A. Guillaume
8. Thomas Blaschke

Citations in the corpus

• A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis (2014, methodology): “This approach makes use of the MCS method by estimating distributions of the output variables (Espinosa-Paredes et al., 2012).”
• Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force. (2016, background): “[83] Durbach IN, Stewart TJ.”
• An uncertain future, deep uncertainty, scenarios, robustness and adaptation: How do they fit together? (2016, background): “Uncertainty has been considered extensively in the context of environmental and hydrological models for many years (Ascough et al., 2008; Durbach and Stewart, 2012; Refsgaard et al., 2007; Stewart, 2005).”