اخبار و اعلانات

 آمار

تعداد نشریات31
تعداد شماره‌ها834
تعداد مقالات8,015
تعداد مشاهده مقاله14,854,101
تعداد دریافت فایل اصل مقاله9,587,301
RAMEZANZADEH, SAEED, MEMARIANI, AZIZOLLAH, SAATI, SABER. (1384). DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED PROGRAMMING APPROACH. نشریه علمی دانشگاه سیستان و بلوچستان, 2(2), 21-29. doi: 10.22111/ijfs.2005.479
SAEED RAMEZANZADEH; AZIZOLLAH MEMARIANI; SABER SAATI. "DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED PROGRAMMING APPROACH". نشریه علمی دانشگاه سیستان و بلوچستان, 2, 2, 1384, 21-29. doi: 10.22111/ijfs.2005.479
RAMEZANZADEH, SAEED, MEMARIANI, AZIZOLLAH, SAATI, SABER. (1384). 'DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED PROGRAMMING APPROACH', نشریه علمی دانشگاه سیستان و بلوچستان, 2(2), pp. 21-29. doi: 10.22111/ijfs.2005.479
RAMEZANZADEH, SAEED, MEMARIANI, AZIZOLLAH, SAATI, SABER. DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED PROGRAMMING APPROACH. نشریه علمی دانشگاه سیستان و بلوچستان, 1384; 2(2): 21-29. doi: 10.22111/ijfs.2005.479

DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED PROGRAMMING APPROACH

Iranian Journal of Fuzzy Systems
مقاله 4، دوره 2، شماره 2، دی 2005، صفحه 21-29    اصل مقاله (291.99 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/ijfs.2005.479
نویسندگان
SAEED RAMEZANZADEH* 1؛ AZIZOLLAH MEMARIANI2؛ SABER SAATI3
1DEPARTMENT OF MATHEMATICS, POLICE UNIVERSITY, TEHRAN, IRAN
2DEPARTMENT OF INDUSTRIAL ENGINEERING, BU-ALI SINA UNIVERSITY, HAMEDAN, IRAN
3DEPARTMENT OF MATHEMATICS, TEHRAN NORTH BRANCH, ISLAMIC AZAD UNIVERSITY, TEHRAN, IRAN
چکیده
In this paper, we deal with fuzzy random variables for inputs and
outputs in Data Envelopment Analysis (DEA). These variables are considered as fuzzy
random flat LR numbers with known distribution. The problem is to find a method for
converting the imprecise chance-constrained DEA model into a crisp one. This can be
done by first, defuzzification of imprecise probability by constructing a suitable
membership function, second, defuzzification of the parameters using an α-cut and
finally, converting the chance-constrained DEA into a crisp model using the method
of Cooper [4].
کلیدواژه‌ها
Data Envelopment Analysis؛ Chance-constrained DEA؛ Fuzzy random variable؛ Triangular fuzzy number
مراجع
[1] A. Charnes, W. W. Cooper and G. Yu, Models for dealing with imprecise data in DEA, Managment
Science, 45 (1999) 597-607.
[2] D. Chakraborty, J. R. Rao and R. N. Tiwari, Multiobjective imprecise chance-constrained
programming problem, J. Fuzzy Math, 1 (2) (1993) 377–387. Corrigendum to: Multiobjective
imprecise-chance constrained programming problem, J. Fuzzy Math, 2 (1) (1994) 231–232.
[3] D. Chakraborty, Redefining chance-constrained programming in fuzzy environment, Fuzzy Sets and
Systems , 125 (2002) 327-333.
[4] W. W. Cooper, H. Deng, Z. M. Huang and S. X. Li, Satisfying DEA models under Chance constraints,
The Annals of Operations Research, 66 (1996a) 279-295.

[5] W. W. Cooper, H. Deng, Z. M. Huang and S. X. Li, Chance constrained programming approaches to
technical efficiencies and inefficiencies in stochastic data envelopmaent analysis, Journal of the
Operational Research Society, 53 (2002a) 1347-1356.
[6] W. W. Cooper, H. Deng, Z. M. Huang and S. X. Li, Chance constrained programming approaches to
congestion in stochastic data envelopmaent analysis, European Journal of Operational Research,
155 (2004) 487-501.
[7] W. Guangyvan and Z. Yue, The theory of fuzzy stochastic processes, Fuzzy Sets and Systems, 51
(1992) 161-178.
[8] W. Guangyuan and Q. Zhong, Linear programming with fuzzy random variable coefficients, FSS, 57
(1993) 295-311.
[9] P. Gao and H. Tanaka, Fuzzy DEA : A pereceptual evaluation method, Fuzzy Sets and Systems, 119
(2001) 149-160.
[10] J. L. Hougaard, Fuzzy scores of technical efficiency, European Journal of Operation Research, 115
(1999).
[11] P. Kall and S. W. Wallace, Stochastic Programming, John Wiley &Sons, New York, 1994.
[12] C. Kao and S. T. Liu, Fuzzy Efficiency Measures in Data Envelopment Analysis, Fuzzy Sets and
Systems, 113 (2000) 529-541.
[13] H. Kwakernaak, Fuzzy random variables, definitions and theorems, Inf. Sci., 15 (1978) 1-29.
[14] B. Liu, Fuzzy random chance-constrained programming, IEEE Transactions on Fuzzy Systems, 9 (5)
(2001) 713–720.
[15] B. Liu, Fuzzy random dependent-chance programming, IEEE Transactions on Fuzzy Systems, 9 (5)
(2001) 721–726.
[16] M.K. Luhandjula, Fuzziness and randomness in an optimization framework, Fuzzy Sets and Systems,
77 (1996) 291–297.
[17] M. K. Luhandjula and M. M.Gupta, On fuzzy stochastic optimization, Fuzzy Sets and Systems, 81
(1996) 47–55.
[18] O.B. Olesen and N. C. Petersen, Chance constrained efficiency evaluation, Management Science,
41 (1995) 442-457.
[19] M. L. Puri and D.A. Ralescu, Fuzzy random variables, J.Math. Anal. Appl., 114 (1986) 409-422.
[20] S. Saati, A. Memariani and G. R. Jahanshahloo, Efficiency analysis and ranking of DMUs with fuzzy
data, Fuzzy Optimization and Decision Making, 1 (2002) 255-256.
[21] B. Seaver and K. Triantis, A fuzzy clustering approach used in evaluating technical efficiency measures
in manufacturing, Journal of productivity Analysis, 3 (1992) 337-363.
[22] J. K. Sengupta, A Fuzzy System Approach in Data Envelopment Analysis, Computers Math. Applic. 24
(1992).

آمار
تعداد مشاهده مقاله: 2,811
تعداد دریافت فایل اصل مقاله: 2,332


سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب