Randomized crossover efficiency in evaluating decision units with unfavorable factors
Subject Areas :
mehdi khodadadipour
1
(Department of management.Dehaghan Branch.Islamic Azad University.Dehaghan .Iran)
sayyed mohammadreza davoodi
2
(Associate management.Dehaghan Branch.Islamic Azad University.Dehaghan .Iran)
Keywords: Data envelopment analysis (DEA), input-oriented CCR model , Stochastic Cross-efficiency evaluation, Undesirable outputs, ranking criterion,
Abstract :
abstract: In this article, using the input-oriented multiple CCR model with undesirable outputs, taking into account the specific error, and using statistical techniques and normal distribution, a new random model is proposed under the title of average rating criterion to evaluate the efficiency of random data. Also, in the random crossover efficiency for ranking DMUs in the coverage analysis of random data is defined based on random limit programming and average value, and since the optimal weights are not unique, an arbitrary method is suggested for better ranking and prioritizing them. Finally, the proposed models for the number of 32 thermal power plants in Angola between 2010 and 2022, which produce energy and have desirable inputs and random desirable and undesirable outputs, were implemented and executed. The results showed that in using the proposed models, the random efficiency of DMUs for separation and ranking has been done with greater power.
