Robust ordinal regression for value functions handling interacting criteria
نویسندگان
چکیده
منابع مشابه
Handling imprecise evaluations in multiple criteria decision aiding and robust ordinal regression by n-point intervals
We consider imprecise evaluation of alternatives in multiple criteria ranking problems. The imprecise evaluations are represented by n-point intervals which are defined by the largest interval of possible evaluations and by its subintervals sequentially nested one in another. This sequence of subintervals is associated with an increasing sequence of plausibility, such that the plausibility of a...
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We present a new method, called UTA, for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. The preference information provided by the decision maker is a set of pairwise comparisons on a subset of alternatives A A, called reference alternatives. The preference model built via ordinal regression is the set of all...
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Making any type of decision, from buying a car to siting a nuclear plant, from choosing the best student deserving a scholarship to ranking the cities of the world according to their liveability, involves the evaluation of several alternatives with respect to different aspects, technically called evaluation criteria. Multiple Criteria Decision Aiding (MCDA) (see [13, 14]) provides methodologies...
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Article history: Received 25 October 2010 Accepted 31 March 2011 Available online 8 April 2011
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Within the multicriteria aggregation-disaggregation framework, ordinal regression aims at inducing the parameters of a decision model, for example those of a utility function, which have to represent some holistic preference comparisons of a Decision Maker (DM). Usually, among the many utility functions representing the DM’s preference information, only one utility function is selected. Since s...
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ژورنال
عنوان ژورنال: European Journal of Operational Research
سال: 2014
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2014.05.022