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Sensitivity Analysis of Inefficient Decision-Making Units in Data Envelopment Analysis (DEA) with a Focus on Boilers: A Case Study
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Abstract
This paper focuses on the sensitivity analysis of inefficient Decision-Making Units (DMUs) in Data Envelopment Analysis (DEA), particularly on boilers. The main objective of this study is to identify and evaluate the efficiency of boilers across various industries and to propose a modified model for their sensitivity analysis. Boiler performance criteria are inputs and outputs, and a case study is presented within an industrial plant. The paper introduces an enhanced DEA-based model to assess the sensitivity of inefficient boilers. The proposed model determines the instability radius of boilers concerning changes in inputs and outputs. Employing managerial coefficients offers greater flexibility in adapting strategies. A case study is implemented in a power plant.
Keywords
Data envelopment analysis Power plant boilers Efficient and inefficient decision-making units Counterparty credit risk Bidirectional consistency constraintReferences (15)
- [1] Ashokkumar, A. (2012). Improvement of boiler efficiency in thermal power plants. Middle-east journal of scientific research, 12(12), 1675–1677. https://doi.org/10.5829/idosi.mejsr.2012.12.12.23
- [2] Liu, X., & Bansal, R. (2012). Improving fossil fuel boiler combustion efficiency based on integrating real time simulation with online learning technology. International journal of ambient energy, 33(3), 130–141. https://doi.org/10.1080/01430750.2012.686193
- [3] Xin, P., Kai, Z., & others. (2011). Hybrid modeling optimization of thermal efficiency and NOx emission of utility boiler. Proceedings of the csee, 31(26), 16–22. https://dx.doi.org/10.13334/j.0258-8013.pcsee.2011.26.009
- [4] Chandel, R., Singh, H., & Kumar, R. (2017). Performance evaluation of state-owned thermal power plants in northern India using DEA. International journal of global energy issues, 40(6), 380–399. https://doi.org/10.1504/IJGEI.2017.089611
- [5] Shureshjani, R. A., Askarinejad, S., & Foroughi, A. A. (2022). Evaluating the efficiency of decision making units in fuzzy two-stage DEA models. Fuzzy information and engineering, 14(3), 291–313. https://doi.org/10.1080/16168658.2022.2152921
- [6] Javaherian, N., Hamzehee, A., & Sayyadi Tooranloo, H. (2021). Designing an intuitionistic fuzzy network data envelopment analysis model for efficiency evaluation of decision-making units with two-stage structures. Advances in fuzzy systems, 2021(1), 8860634. https://doi.org/10.1155/2021/8860634
- [7] Toloo, M., & Hančlová, J. (2020). Multi-valued measures in DEA in the presence of undesirable outputs. Omega, 94, 102041. https://doi.org/10.1016/j.omega.2019.01.010
- [8] Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
- [9] Charnes, A., Cooper, W. W., Lewin, A. Y., Morey, R. C., & Rousseau, J. (1984). Sensitivity and stability analysis in DEA. Annals of operations research, 2(1), 139–156. https://doi.org/10.1007/BF01874736
- [10] Neralic, L. (1997). Sensitivity in data envelopment analysis for arbitrary perturbations of data. Glasnik matematicki, 32(2), 315–335. https://B2n.ir/xy1946
- [11] Seiford, L. M., & Zhu, J. (1998). Stability regions for maintaining efficiency in data envelopment analysis. European journal of operational research, 108(1), 127–139. https://doi.org/10.1016/S0377-2217(97)00103-3
- [12] Cooper, W. W., Li, S., Seiford, L. M., Tone, K., Thrall, R. M., & Zhu, J. (2001). Sensitivity and stability analysis in DEA: Some recent developments. Journal of productivity analysis, 15, 217–246. https://doi.org/10.1023/A:1011128409257
- [13] Hibiki, N., & Sueyoshi, T. (1999). DEA sensitivity analysis by changing a reference set: Regional contribution to Japanese industrial development. Omega, 27(2), 139–153. https://doi.org/10.1016/S0305-0483(98)00034-6
- [14] Benicio, J., & Mello, J. C. S. (2019). Different types of return to scale in DEA. Pesquisa operacional, 39, 245–260. https://doi.org/10.1590/0101-7438.2019.039.02.0245
- [15] Barnum, D., Coupet, J., Gleason, J., McWilliams, A., & Parhankangas, A. (2017). Impact of input substitution and output transformation on data envelopment analysis decisions. Applied economics, 49(15), 1543–1556. https://doi.org/10.1080/00036846.2016.1221042