ارائه روشی چند مرحله ای از وزن مشترک و TOPSIS به منظور رتبه بندی واحدها

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استادیار، گروه مدیریت، دانشگاه آزاد اسلامی واحد سمنان، ایران

2 دانشجوی کارشناسی ارشد مدیریت، دانشگاه آزاد اسلامی واحد سمنان، ایران

چکیده

در ارزیابی سازمان ها و نهادها، یکی از مهم ترین اهداف، رتبه بندی واحدها بر اساس میزان عملکرد می باشد. با توجه به این که روش های رایج ارزیابی واحدهای تصمیم گیری در تحلیل پوششی داده ها ممکن است به چندین واحد کارا ختم گردد، همواره انتخاب بهترین واحد از بین تمام واحدها، یکی از مشکلات اصلی در تحلیل پوششی داده هاست. روش های متعددی برای رتبه بندی واحدهای تصمیم گیرنده ارائه شده است. در این مقاله، یکی از روش های جدید به نام وزن مشترک با جزییات مورد بررسی قرار گرفته است. دو روش وزن مشترک و تاپسیس بر روی داده‌های واقعی مربوط به ‎17 بانک در استان سمنان بررسی شده است. نتایج نشان دهنده این است که هر دو روش به رتبه بندی کاملی دست یافته اند، اما در مقایسه بین دو روش نتایج بیانگر این امر است که رتبه بندی با وزن مشترک همخوانی بیشتری با واقعیت دارد. به علاوه روش وزن مشترک غیر پارامتری می باشد و بر اساس کارایی (نسبی) واحدهای کارا، رتبه بهتری کسب نموده است. در روش پیشنهادی همه واحدهای تصمیم گیری با هم در نظر گرفته شده اند، در حالی که در تاپسیس این گونه نیست.

کلیدواژه‌ها


عنوان مقاله [English]

Representing a Multi-Step Technique of the Common weights and TOPSIS in order to Ranking of Units

نویسندگان [English]

  • Mohammad Hemati 1
  • Saeedeh Abbasi 2
1 Assistant Professor, Management Department, Semnan Branch, Islamic Azad University, Semnan, Iran.
2 MA Student in Management, Semnan Branch, Islamic Azad University, Semnan, Iran
چکیده [English]

In evaluating of organizations and institutions, one of the most important goals is the ranking of the units based on the performance of them. According to the commonly used method of decision-making in data envelopment analysis, it may lead to multiple efficient units that choose the best of units, is the main problems in data envelopment analysis. In this paper, a new method as the common weights has been studied in details. Two techniques (common weight and TOPSIS) have been studied on real data of the 17 banks in Semnan province. The results indicate that the two methods have achieved perfect ratings. By comparing the two methods, results have been showed that the common weights rating is closer to reality. In addition, common weight is a non-parametric method and has received a better ranking based on the performance (relative) efficient. Also, in the common weight all of the decisions making have taken together, while in the TOPSIS mode is not.

کلیدواژه‌ها [English]

  • DEA
  • TOPSIS
  • Ranking
  • common weights

[1]       Charnes A., Cooper W. W., Rhodes E. (1978) "Measuring the efficiency of decision making units", European Journal of Operational Research 2: 429-444.

[2]       Liu J., Tone K. (2008) "A multistage method to measure efficiency and its application to Japaness banking industry", Original Research Article Socio-Economic Planning Sciences, 42(2): 75-91.

[3]       Sun J., Wua J., Guo D. (2013) "Performance ranking of units considering ideal and anti-ideal DMU with common weights", Applied Mathematical Modelling, 37)9) :6301-6310.

[4]       Adler N., Friedman L. (2002) "Review of ranking methods in the data envelopment analysis context", European Jurnal of Operational Research 140: 249-265.

[5]       Charnes W. W., Cooper A. Y., Lewin L. M. (1985) Data envelopment Analysis theory, methodology, and application, Kluwer Academic Publishers, London, pp. 97-393.

[6]       Wang Y. M., Chin K. S., Luo Y. (2011) "Cross-efficiency evaluation based on ideal and anti-ideal decision making units", Expert Systems with Applications, 38: 10312–10319.

[7]       János F., Rita M. S. (2012) "Ranking decision making units based on DEA-like nonreciprocal pairwise comparisons", Acta Polytechnica Hungarica, 9 (2) : 77-94.

[8]       Alcaraz J., Ramón N., Ruiz J. L., Sirvent I. (2013) "Ranking ranges in cross-efficiency evaluations", European Journal of Operational Research 222(3): 516-521.

[9]       Rezai Balf F., Zhiani Rezai H., Jahanshahloo G. R., Hosseinzadeh Lotfi, G. R. (2012) "Ranking efficient DMUs using the Tchebycheff norm", Applied Mathematical Modelling, 36: 46–56.

[10]   Mirhashemi A., Izadikhah M. (2013) "Ranking DMUs in the presence of undesirable data", J. Basic. Appl. Sci. Res., 3 (4): 910-919.

[11]   Hosseinzadeh L. F., Malkhalifeh M. R., Heydari Alvar M. (2012) "A new method for ranking efficient DMUs based on TOPSIS and virtual DMUs", Int. J. Research inIndustrial Engineering, 1 (1): 1- 9.

[12]   Azizi H. (2012) "Efficiency assessment in data envelopment analysis using efficient and inefficient frontiers", Journal of Management Research in Iran, 16(3):153-173.

[13]   Mirghafoori S. H., Roodposhti M. S., Ghazaleh G. (2013) "Financial performance evaluating with grey theory and data envelopment analysis technique two step approach (Case study: Province telecommunication companies)", Journal of Management Research in Iran, 16 (4): 189-205.

[14]   Azizi H., Jahed R. (2015) "Supplier selection in volume discount environments in the presence of both cardinal and ordinal data: A new approach based on double frontiers DEA", Journal of Management Research in Iran, 19(3): 191-217.

[15]   Wen M., Li H. (2009)"Fuzzy data envelopment analysis(DEA):Model and ranking method", Journal of computational and applied mathematics, 223(2): 872-878.

[16]   Ranjbar H. (2013)"Ranking of stochastic DEA with using an integrated method using Data envelopment analysis and Fuzzy preference relations", Scholars Journal of Engineeringand Technology,1(4): 232-237.

[17]   Wen M., Qin Zh., Kang R. (2013)"Some new ranking criteria in data envelopment analysis under uncertain environment", Rough Manuscripts of Uncertainty TheoryLaboratory, Online Papers on http://orsc.edu.cn/online/.

[18]   Hamidi N., Shemirani R. A., Shirdel G., Taleshi B. (2012) "Election of optimal supplier using a hybrid fuzzy model based on criteria interrelationship: A case study of an Iranian braking system manufacturer company", Journal of Management Research in Iran, 16(3): 59-81.

[19]   Alirezaee, M. R.; Afsharian M. (2007) "A complete ranking of DMUs using restrictions in DEA models", Applied Mathematics and Computation, 189(2): 1550–1559.

[20]   Mirdehghan S. M., Shirzadi A. (2012) "Ranking decision making units based on the cost efficiency measure", International Journal of Pure and Applied Mathematics, 81(1): 55-63.

[21]   Wang Y. M., Luo Y. (2006) "DEA efficiency assessment using ideal and anti-ideal decision making units", Appl. Math. Comput, 173: 902–915.

[22]   Liu F. H. F., Peng H. H. (2008) "Ranking of units on the DEA frontier with common weights", ComputersOperations Research, 35: 1624 – 1637.

[23]   Jahanshahloo G. R., Hosseinzadeh Lotfi F., Khanmohammadi M., Kazemimanesh M., Rezaie V. (2010) "Ranking of units by positive ideal DMU with common weights", Expert Systems with Applications, 37: 7483–7488.

[24]   Hosseinzadeh Lotfi F., Izadikhah M., Roostaee R., Rostamy Malkhalifeh M. (2012) "A goal programming procedure for ranking decision making units in DEA", MathematicsScientific Journal, 7 (2): 19-38.

[25]   Payan A., Noora A. A., Hosseinzadeh Lotfi Farhad (2014)" A ranking method based on common weights and benchmark point", Applications and AppliedMathematics: an International Journal, 9(1): 318-329.

[26]   Barzegarinegad A., Jahanshahloo G., Rostamy-Malkhalifeh M. (2014)" A full ranking for decision making units using ideal and anti-ideal points in DEA", Hindawi Publishing Corporation The Scientific World Journal, pp: 1-8 .