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A Chance-Constrained Inverse DEA Approach under Managerial and Natural Disposability
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Yasaman Zibaei Vishghaei   , Sohrab Kordrostami , Alireza Amirteimoori , Soheil Shokri |
| Department of Mathematics, Lahijan Branch, Islamic Azad University, Lahijan, Iran , sohrabkordrostami@gmail.com |
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Abstract: (203 Views) |
The traditional inverse data envelopment analysis (IDEA) models assess specific performance metrics in relation to changes in others, without taking into consideration the existence of random and undesirable outputs. This study presents a novel inverse DEA model with random and undesirable outputs, enabling the estimation of some random performance measures for changes of other random measures. The proposed chance-constrained inverse DEA model integrates both managerial and natural disposability constraints. By using the introduced approach, the estimation of natural disposable random inputs is presented for changes in random desirable outputs. Also, undesirable outputs are assessed for the perturbation of managerial disposable random inputs while the stochastic efficiency is maintained. The models are solved as linear problems, with a numerical example provided to illustrate their application. The findings indicate that this approach is effective for evaluating efficiency and performance metrics in scenarios involving random and undesirable outputs.
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| Keywords: Inverse DEA, Chance-Constrained DEA, Undesirable Outputs, Managerial Disposability |
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Full-Text [PDF 355 kb]
(195 Downloads)
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Type of Study: Original |
Subject:
Mathematical Modeling and Applications of OR
Received: 2024/06/2 | Accepted: 2024/07/24 | Published: 2024/09/2
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