efficiency evaluation and ranking dmus in the presence of interval data with stochastic bounds
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abstract
on account of the existence of uncertainty, dea occasionally faces the situation of imprecise data, especially when a set of dmus include missing data, ordinal data, interval data, stochastic data, or fuzzy data. therefore, how to evaluate the efficiency of a set of dmus in interval environments is a problem worth studying. in this paper, we discussed the new method for evaluation and ranking interval data with stochastic bounds. the approach is exemplified by numerical examples.
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Journal title:
international journal of data envelopment analysisISSN 2345-458X
volume 3
issue 1 2015
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