Numerical Algebra, Control and Optimization (NACO)

Performance evaluation of four-stage blood supply chain with feedback variables using NDEA cross-efficiency and entropy measures under IER uncertainty
Pages: 379 - 401, Issue 4, December 2017

doi:10.3934/naco.2017024      Abstract        References        Full text (381.9K)           Related Articles

Shiva Moslemi - Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran (email)
Abolfazl Mirzazadeh - Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran (email)

1 J. C. Baez, T. Fritz and T. Leinster, A characterization of entropy in terms of information loss, Entropy, 13 (2011), 1945-1957.       
2 J. Beliën and H. Forcé, Supply chain management of blood products: A literature review, European Journal of Operational Research, 217 (2012), 1-16.       
3 C. Chen and H. Yan, Network DEA model for supply chain performance evaluation, European Journal of Operational Research, 213 (2011), 147-155.       
4 K. S. Chin, Y. M. Wang, J. B. Yang and K. K. G. Poon, An evidential reasoning based approach for quality function deployment under uncertainty, Expert Systems with Applications, 36 (2009), 5684-5694.
5 M. A. Cohen and W. P. Pierskalla, Management policies for a regional blood bank, Transfusion, 15 (1975), 58-67.
6 W. W. Cooper, K. S. Park and G. Yu, IDEA and AR-IDEA: Models for dealing with imprecise data in DEA, Management science, 45 (1999), 597-607.
7 M. Dotoli, N. Epicoco and M. Falagario, A technique for supply chain network design under uncertainty using cross-efficiency fuzzy data envelopment analysis, IFAC-PapersOnLine, 48 (2015), 634-639.
8 J. Doyle and R. Green, Efficiency and cross-efficiency in DEA: Derivations,meanings and uses, Journal of the Operational Research Society, 45 (1994), 567-578.
9 M. Guo, J. B. Yang, K. S. Chin, H. W. Wang and X. B. Liu, Evidential reasoning approach for multiattribute decision analysis under both fuzzy and interval uncertainty, IEEE Transactions on Fuzzy Systems, 17 (2009), 683-697.
10 A. Hatami-Marbini, P. J. Agrell, M. Tavana and P. Khoshnevis, A flexible cross-efficiency fuzzy data envelopment analysis model for sustainable sourcing, Journal of Cleaner Production, 142 (2017), 2761-2779.
11 G. R. Jahanshahloo, M. Khodabakhshi, F. H. Lotfi and M. M. Goudarzi, A cross-efficiency model based on super-efficiency for ranking units through the TOPSIS approach and its extension to the interval case, Mathematical and Computer Modelling, 53 (2011), 1946-1955.       
12 C. Kao, Efficiency decomposition for general multi-stage systems in data envelopment analysis, European Journal of Operational Research, 232 (2014), 117-124.       
13 K. Katsaliaki, Cost-effective practices in the blood service sector, Health policy, 86 (2008), 276-287.
14 S. Keikha-Javan and M. Rostamy-Malkhalifeh, Efficiency measurement of NDEA with interval data, International Journal of Mathematical Modelling and Computations, 6 (2016), 199-210.
15 K. Khalili-Damghani and M. Taghavifard, A three-stage fuzzy DEA approach to measure performance of a serial process including JIT practices, agility indices, and goals in supply chains, International Journal of Services and Operations Management, 13 (2012), 147-188.
16 K. Khalili-Damghani, M. Taghavi-Fard and A. R. Abtahi, A fuzzy two-stage DEA approach for performance measurement: real case of agility performance in dairy supply chains, International Journal of Applied Decision Sciences, 5 (2012), 293-317.
17 L. Liang, Z. Q. Li, W. D. Cook and J. Zhu, Data envelopment analysis efficiency in two-stage networks with feedback, IIE Transactions, 43 (2011), 309-322.
18 C. lo Storto, Ecological efficiency based ranking of cities: A combined DEA cross-efficiency and Shannon's entropy method, Sustainability, 8 (2016), 124.
19 F. H. Lotfi, M. Navabakhs, A. Tehranian, M. Rostamy-Malkhalifeh and R. Shahverdi, Ranking bank branches with interval data-The application of DEA, In International Mathematical Forum, 2 (2007), 429-440.       
20 T. Lu and S. T. Liu, Ranking DMUs by comparing DEA cross-efficiency intervals using entropy measures, Entropy, 18 (2016), 452.
21 A. M. Mathai and H. J. Haubold, On a generalized entropy measure leading to the pathway model with a preliminary application to solar neutrino data, Entropy, 15 (2013), 4011-4025.       
22 S. M. Mirhedayatian, M. Azadi and R. F. Saen, A novel network data envelopment analysis model for evaluating green supply chain management, International Journal of Production Economics, 147 (2014), 544-554.
23 K. H. Mistry and J. H. Lienhard, An economics-based second law efficiency, Entropy, 15 (2013), 2736-2765.       
24 A. F. Osorio, S. C. Brailsford and H. K. Smith, A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making, International Journal of Production Research, 53 (2015), 7191-7212.
25 A. Pereira, Economies of scale in blood banking: a study based on data envelopment analysis, Vox Sanguinis, 90 (2006), 308-315.
26 C. Pitocco and T. R. Sexton, Alleviating blood shortages in a resource-constrained environment, Transfusion, 45 (2005), 1118-1126.
27 G. B. Schreiber, K. S. Schlumpf, S. A. Glynn, D. J. Wright, Y. Tu, M. R. King, M.J. Higgins, D. Kessler, R. Gilcher, C. C. Nass and A. M. Guiltinan, Convenience, the bane of our existence, and other barriers to donating, Transfusion, 46 (2006), 545-553.
28 T. R. Sexton, R. H. Silkman and A. J. Hogan, Data envelopment analysis: Critique and extensions, New Directions for Evaluation, 32 (1986), 73-105.
29 G. Shafer, A Mathematical Theory of Evidence, Princeton: Princeton University Press, 1976.       
30 Y. S. Shao and D. Brooks, ISA-independent workload characterization and its implications for specialized architectures,, in Performance Analysis of Systems and Software (ISPASS), 2013 IEEE International Symposium on. IEEE, (2013), 245-255.
31 M. Tavana, H. Mirzagoltabar, S. M. Mirhedayatian, R. F. Saen and M. Azadi, A new network epsilon-based DEA model for supply chain performance evaluation, Computers and Industrial Engineering, 66 (2013), 501-513.
32 Y. M. Wang and K. S. Chin, A neutral DEA model for cross-efficiency evaluation and its extension, Expert Systems with Applications, 37 (2010a), 3666-3675.
33 Y. M. Wang and K. S. Chin, Some alternative models for DEA cross-efficiency evaluation, International Journal of Production Economics, 128 (2010b), 332-338.
34 L. Wang, L. Li and N. Hong, Entropy cross-efficiency model for decision making units with interval data, Entropy, 18 (2016), 358.
35 B. Y. Wong, J. B. Yang and R. Greatbanks, Using DEA and the ER approach for performance measurement of UK retail banks, MCDM, (2004), 6-11.
36 J. Wu, L. Liang and F. Yang, Determination of the weights for the ultimate cross efficiency using Shapley value in cooperative game, Expert Systems with Applications, 36 (2009), 872-876.
37 J. Wu, J. S. Sun, L. A. Liang and Y. C. Zha, Determination of weights for ultimate cross efficiency using Shannon entropy, Expert Syst. Appl., 38 (2011), 5162-5165.
38 J. Wu, J. S. Sun and L. Liang, DEA cross-efficiency aggregation method based upon Shannon entropy, Int. J. Prod. Res., 50 (2012), 6726-6736.
39 F. Yang, S. Ang, Q. Xia and C. Yang, Ranking DMUs by using interval DEA cross efficiency matrix with acceptability analysis, European Journal of Operational Research, 223 (2012), 483-488.       
40 J. B. Yang and M. G. Singh, An evidential reasoning approach for multiple-attribute decision making with uncertainty, IEEE Transactions on systems, Man, and Cybernetics, 24 (1994), 1-18.
41 J. B. Yang, Y. M. Wang, D. L. Xu and K. S. Chin, The evidential reasoning approach for MADA under both probabilistic and fuzzy uncertainties, European journal of operational research, 171 (2006), 309-343.       
42 G. L. Yang, J. B. Yang, W. B. Liu and X. X. Li, Cross-efficiency aggregation in DEA models using the evidential-reasoning approach, European Journal of Operational Research, 231 (2013), 393-404.       
43 Q. Yu and F. Hou, A cross evaluation-based measure of super efficiency in DEA with interval data, Kybernetes, 45 (2016), 666-679.       
44 Y. Zha, X. Ding, L. Liang and Z. Huang, A two-stage DEA approach with feedback for team performance evaluation, In Applications of Management Science. Emerald Group Publishing Limited, (2012), 3-18.

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