Factors affecting deviations of efficiency in distance-based Common Set of Weight -DEA models
محورهای موضوعی : Data Envelopment Analysis
سعید شاه قبادی
1
(
.گروه ریاضی کاربردی، واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه، ایران
)
کلید واژه: Data envelopment analysis, Ranking, Common Set of Weights, efficiency evaluation,
چکیده مقاله :
There are different approaches to generate a common set of weights in DEA based on the p - distance measure. Deviation of an efficiency score derived from a CSW from target efficiency score may be related to the model and the parameter p. In this study, we try to clarify points about choosing p, model, and data set if it is necessary to produce an efficiency score with the least deviation by a CSW. Two improved linear models are developed by analyzing the result of available models. The results of the proposed models have smaller individual and overall efficiency than corresponding prior ones that It has been confirmed with numerical examples and simulation analysis.
روشهای مختلفی برای تولید مجموعه ای مشترک از وزنها در تحلیل پوششی داده ها بر اساس اندازه گیری فاصله نرم P وجود دارد. انحراف نمره کارایی حاصل از اوزان مشترک، از نمره کارایی هدف ممکن است مربوط به مدل و پارامتر p باشد. در این مطالعه ، در صورت ایجاد نمره کارایی با کمترین انحراف توسط وزن مشترک ، سعی می شودفاکتور های تاثیرگزار در مورد انتخاب p ، مدل و مجموعه داده ها تععین شود.همچنین با تجزیه و تحلیل نتیجه مدل های موجود ، دو مدل خطی بهبود یافته معرفی شده است.نتایج مدلهای پیشنهادی دارای انحرافات کارایی فردی و کلی کمتری نسبت به مدلهای قبلی است که این نتایج با مثالهای عددی و تجزیه و تحلیل شبیه سازی تأیید شده است.
Aldamak, A. and S. Zolfaghari (2017). "Review of efficiency ranking methods in data envelopment analysis." Measurement 106: 161-172.
Amin, G. R. and M. Toloo (2004). "A polynomial-time algorithm for finding ε in DEA models." Computers & Operations Research 31(5): 803-805.
Charnes, A., W. W. Cooper and E. Rhodes (1978). "Measuring the efficiency of decision making units." European Journal of Operational Research 2(6): 429-444.
Chen, Y. W., M. Larbani and Y. P. Chang (2009). "Multiobjective data envelopment analysis." Journal of the Operational Research Society 60(11): 1556-1566.
Cook, W. D. and L. Seiford (2009). "Data envelopment analysis (DEA) - Thirty years on." European Journal of Operational Research 192(1): 1-17.
Cooper, W. W., L. M. Seiford and K. Tone (2007). Data envelopment analysis a comprehensive text with models, applications, references and DEA-solver software. New York (Estados Unidos, Springer.
Hosseinzadeh Lotfi, F., G. Jahanshahloo, M. Vaez-Ghasemi and Z. Moghaddas (2013). "Modified Malmquist Productivity Index Based on Present Time Value of Money." Journal of Applied Mathematics 2013: 607190.
Hosseinzadeh Lotfi, F., G. R. Jahanshahloo, M. Vaez-Ghasemi and Z. Moghaddas (2013). "Evaluation progress and regress of balanced scorecards by multi-stage Malmquist Productivity Index." Journal of Industrial and Production Engineering 30(5): 345-354.
Izadikhah, M. and R. Farzipoor Saen (2019). "Solving voting system by data envelopment analysis for assessing sustainability of suppliers." Group Decision and Negotiation 28(3): 641-669.
Kao, C. and H. T. Hung (2005). "Data envelopment analysis with common weights: the compromise solution approach." Journal of the Operational Research Society 56(10): 1196-1203.
Kornbluth, J. S. H. (1991). "Analysing Policy Effectiveness Using Cone Restricted Data Envelopment Analysis." Journal of the Operational Research Society 42(12): 1097-1104.
Lotfi, F. H., A. Ebrahimnejad, M. Vaez-Ghasemi and Z. Moghaddas Data envelopment analysis with R, Springer.
Pourhabib Yekta, A., S. Kordrostami, A. Amirteimoori and R. Kazemi Matin (2018). "Data envelopment analysis with common weights: the weight restriction approach." Mathematical Sciences 12(3): 197-203.
Roll, Y., W. D. Cook and B. Golany (1991). "Controlling Factor Weights in Data Envelopment Analysis." IIE Transactions 23(1): 2-9.
Shahghobadi, S. (2020). "Utilization of performance indicators in data envelopment analysis to increase the efficiency discrimination of units." Computers & Industrial Engineering 145: 106535.
Soltanifar, M. and S. Shahghobadi (2013). "Selecting a benevolent secondary goal model in data envelopment analysis cross-efficiency evaluation by a voting model." Socio-Economic Planning Sciences 47(1): 65-74.
Soltanifar, M. and S. Shahghobadi (2014). "Survey on rank preservation and rank reversal in data envelopment analysis." Knowledge-Based Systems 60: 10-19.
Sun, J., J. Wu and D. Guo (2013). "Performance ranking of units considering ideal and anti-ideal DMU with common weights." Applied Mathematical Modelling 37(9): 6301-6310.
Zohrehbandian, M., A. Makui and A. Alinezhad (2010). "A compromise solution approach for finding common weights in DEA: an improvement to Kao and Hung's approach." Journal of the Operational Research Society 61(4): 604-610.
