Subject Areas : International Journal of Data Envelopment Analysis
Mohammad Taghi Yahyapour-Shikhzahedi 1 , sohrab kordrostami 2 , S Edalatpanah 3 , Alireza Amirteimoori 4
1 - گروه ریاضی، واحد لاهیجان،دانشگاه آزاد اسلامی، لاهیجان، ایران.
2 - Department of mathematics, Islamic azad University of Lahijan, Lahjan, Iran
3 - Islamic Azad University, Iran
4 - Department of Applied Mathematics, Lahijan Branch, Islamic Azad University, Lahijan, Iran
Keywords:
Abstract :
1. Ebrahimnejad, A., Nasseri, S.H., Lotfi, F.H., Soltanifar, M.: A primal-dual method for linear programming problems with fuzzy variables. European J. of Industrial Engineering. 4, 189 (2010). https://doi.org/10.1504/EJIE.2010.031077
2. Jiménez, M., Arenas, M., Bilbao, A., Rodrı´guez, M.V.: Linear programming with fuzzy parameters: An interactive method resolution. Eur J Oper Res. 177, 1599–1609 (2007). https://doi.org/10.1016/j.ejor.2005.10.002
3. Maleki, H.R., Tata, M., Mashinchi, M.: Linear programming with fuzzy variables. Fuzzy Sets Syst. 109, 21–33 (2000). https://doi.org/10.1016/S0165-0114(98)00066-9
4. Rommelfanger, H.: A general concept for solving linear multicriteria programming problems with crisp, fuzzy or stochastic values. Fuzzy Sets Syst. 158, 1892–1904 (2007). https://doi.org/10.1016/j.fss.2007.04.005
5. Maleki, H.R.: Ranking Functions and Their Applications to Fuzzy Linear Programming. Far East Journal of Mathematical Sciences. 283-301. . 4, 283–301 (2002)
6. Ramik, J.: Duality in Fuzzy Linear Programming: Some New Concepts and Results. Fuzzy Optimization and Decision Making. 4, 25–39 (2005). https://doi.org/10.1007/s10700-004-5568-z
7. Ganesan, K., Veeramani, P.: Fuzzy linear programs with trapezoidal fuzzy numbers. Ann Oper Res. 143, 305–315 (2006). https://doi.org/10.1007/s10479-006-7390-1
8. Nasseri, S.H., Mahmoudi, F.: A New Approach to Solve Fully Fuzzy Linear Programming Problem. Journal of Applied Research on Industrial Engineering. 6, 139–149 (2019)
9. Ezzati, R., Khorram, E., Enayati, R.: A new algorithm to solve fully fuzzy linear programming problems using the MOLP problem. Appl Math Model. 39, 3183–3193 (2015). https://doi.org/10.1016/j.apm.2013.03.014
10. Edalatpanah, S.A.: A Direct Model for Triangular Neutrosophic Linear Programming . International Journal of Neutrosophic Science (IJNS). 1, 19–28 (2020)
11. Kaur, A., Kumar, A.: A new approach for solving fuzzy transportation problems using generalized trapezoidal fuzzy numbers. Appl Soft Comput. 12, 1201–1213 (2012). https://doi.org/10.1016/j.asoc.2011.10.014
12. Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision making units. Eur J Oper Res. 2, 429–444 (1978). https://doi.org/10.1016/0377-2217(78)90138-8
13. Tone, K.: A strange case of the cost and allocative efficiencies in DEA. Journal of the Operational Research Society. 53, 1225–1231 (2002). https://doi.org/10.1057/palgrave.jors.2601438
14. Banker, R.D., Charnes, A., Cooper, W.W.: Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Manage Sci. 30, 1078–1092 (1984). https://doi.org/10.1287/mnsc.30.9.1078
15. Zhang, G., Cui, J.: A general inverse DEA model for non-radial DEA. Comput Ind Eng. 142, 106368 (2020). https://doi.org/10.1016/j.cie.2020.106368
16. Wei, Q., Zhang, J., Zhang, X.: An inverse DEA model for inputs/outputs estimate. Eur J Oper Res. 121, 151–163 (2000). https://doi.org/10.1016/S0377-2217(99)00007-7
17. Yan, H., Wei, Q., Hao, G.: DEA models for resource reallocation and production input/output estimation. Eur J Oper Res. 136, 19–31 (2002). https://doi.org/10.1016/S0377-2217(01)00046-7
18. Hadi-Vencheh, A., Hatami-Marbini, A., Ghelej Beigi, Z., Gholami, K.: An inverse optimization model for imprecise data envelopment analysis. Optimization. 64, 2441–2454 (2015). https://doi.org/10.1080/02331934.2014.974599
19. Lertworasirikul, S., Charnsethikul, P., Fang, S.-C.: Inverse data envelopment analysis model to preserve relative efficiency values: The case of variable returns to scale. Comput Ind Eng. 61, 1017–1023 (2011). https://doi.org/10.1016/j.cie.2011.06.014
20. Farrell, M.J.: The Measurement of Productive Efficiency. J R Stat Soc Ser A. 120, 253 (1957). https://doi.org/10.2307/2343100
21. Fukuyama, H., Weber, W.L.: Estimating output allocative efficiency and productivity change: Application to Japanese banks. Eur J Oper Res. 137, 177–190 (2002)
22. Banihashem, S., Sanei, M., Mohamadian Manesh, Z.: Cost, revenue and profit efficiency in supply chain. African Journal of Business Management. 7, 4280–4287 (2013)
23. Khodabakhshi, M., Aryavash, K.: The fair allocation of common fixed cost or revenue using DEA concept. Ann Oper Res. 214, 187–194 (2014). https://doi.org/10.1007/s10479-012-1117-2
24. Mozaffari, M.R., Kamyab, P., Jablonsky, J., Gerami, J.: Cost and revenue efficiency in DEA-R models. Comput Ind Eng. 78, 188–194 (2014). https://doi.org/10.1016/j.cie.2014.10.001
25. Fang, L., Li, H.: Centralized resource allocation based on the cost–revenue analysis. Comput Ind Eng. 85, 395–401 (2015). https://doi.org/10.1016/j.cie.2015.04.018
26. Amin, G.R., Ibn Boamah, M.: A new inverse DEA cost efficiency model for estimating potential merger gains: a case of Canadian banks. Ann Oper Res. 295, 21–36 (2020). https://doi.org/10.1007/s10479-020-03667-9
27. Chen, S.-P., Hsueh, Y.-J.: A simple approach to fuzzy critical path analysis in project networks. Appl Math Model. 32, 1289–1297 (2008). https://doi.org/10.1016/j.apm.2007.04.009
28. Narayanamoorthy, S., Saranya, S., Maheswari, S.: A Method for Solving Fuzzy Transportation Problem (FTP) using Fuzzy Russell’s Method. International Journal of Intelligent Systems and Applications. 5, 71–75 (2013). https://doi.org/10.5815/ijisa.2013.02.08
29. Charles Rabinson, G., Chandrasekaran, R.: A Method for Solving a Pentagonal Fuzzy Transportation Problem via Ranking Technique and ATM. n, International Journal of Research in Engineering, IT and Social Science. 09, 71–75 (2019)
30. K.Saini, R., Sangal, A., Prakash, O.: Unbalanced Transportation Problems in Fuzzy Environment using Centroid Ranking Technique. Int J Comput Appl. 110, 27–33 (2015). https://doi.org/10.5120/19363-0998