Robustness and sensitivity analysis in multiple criteria decision problems using rule learner techniques

Claudio M. Rocco S. and Elvis Hernandez

Reliability Engineering and System Safety, 2015, vol. 134, issue C, 297-304

Abstract: In many situations, a decision-maker is interested in assessing a set of alternatives characterized simultaneously by multiple criteria (attributes), and defining a ranking able to synthesize the global characteristics of each alternative, for example, from the best to the worst. This is the case of the assessment of several projects through attributes such as cost, profitability, among others. The behavior of each object, for every criterion, is quantified via numerical or categorical “performance values†. Several multiple criteria decision techniques could be used to this aim. However the base rank could be influenced by uncertain factors associated to specific criteria (e.g., the “ratio Benefit/Cost of a project†could be affected by variations in the interest rate) or by decision-maker preferences. In this situation, the decision-maker could be interested knowing what sets of factors are responsible of specific ranking conditions.

Keywords: Monte Carlo simulation; Multiple criteria decision; Rule learners; Uncertainty (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:134:y:2015:i:c:p:297-304

DOI: 10.1016/j.ress.2014.04.022

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