An integrated data envelopment analysis and simulation method for group consensus ranking

Mathematics and Computers in Simulation - Tập 119 - Trang 1-17 - 2016
Ali Ebrahimnejad1, Madjid Tavana2,3, Francisco J. Santos-Arteaga4
1Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran
2Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, PA 19141, USA
3Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, D-33098 Paderborn, Germany
4Departamento de Economía Aplicada II, Facultad de Económicas, Universidad Complutense de Madrid, Campus de Somosaguas, 28223 Pozuelo, Spain

Tài liệu tham khảo

Al-Refaie, 2014, Applying simulation and DEA to improve performance of emergency department in a Jordanian hospital, Simul. Model. Pract. Theory, 41, 59, 10.1016/j.simpat.2013.11.010 Amin, 2010, Application of prioritized aggregation operators in preference voting, Int. J. Intell. Syst., 25, 1027, 10.1002/int.20437 Amirteimoori, 2010, A Euclidean distance-based measure of efficiency in data envelopment analysis, Optimization, 59, 985, 10.1080/02331930902878333 Amirteimoori, 2013, An alternative clustering approach: a DEA-based procedure, Optimization, 62, 227, 10.1080/02331934.2011.585466 Andersen, 1993, A procedure for ranking efficient units in data envelopment analysis, Manage. Sci., 39, 1261, 10.1287/mnsc.39.10.1261 Azadeh, 2014, An integrated fuzzy simulation–fuzzy data envelopment analysis approach for optimum maintenance planning, Int. J. Comput. Integr. Manuf., 27, 181, 10.1080/0951192X.2013.812804 Brams, 2002, Voting procedures, vol. 1, 173 Cook, 1990, A data envelopment model for aggregating preference rankings, Manage. Sci., 36, 1302, 10.1287/mnsc.36.11.1302 Dur, 2005, Producing and manipulating information, Econ. J., 115, 185, 10.1111/j.1468-0297.2004.00965.x Ebrahimnejad, 2012, A new approach for ranking of candidates in voting systems, Opsearch, 49, 103, 10.1007/s12597-012-0070-9 Foroughi, 2012, New approaches for determining a common set of weights for a voting system, Int. Trans. Oper. Res., 19, 521, 10.1111/j.1475-3995.2011.00832.x Foroughi, 2005, A selection method for a preferential election, Appl. Math. Comput., 163, 107, 10.1016/j.amc.2003.10.055 Foroughi, 2005, An effective total ranking model for a ranked voting system, Omega, 33, 491, 10.1016/j.omega.2004.07.013 Fudenberg, 1991 Gilboa, 1989, Maxmin expected utility with non-unique prior, J. Math. Econom., 18, 141, 10.1016/0304-4068(89)90018-9 Green, 1996, Preference voting and project ranking using DEA and cross-evaluation, European J. Oper. Res., 90, 461, 10.1016/0377-2217(95)00039-9 Hashimoto, 1997, A ranked voting system using a DEA/AR exclusion model: A note, European J. Oper. Res., 97, 600, 10.1016/S0377-2217(96)00281-0 Hosseinzadeh Lotfi, 2011, A note on “A solution method to the problem proposed by Wang in voting systems”, Appl. Math. Sci., 5, 3051 Hosseinzadeh Lotfi, 2013, Allocating fixed resources and setting targets using a common-weights DEA approach, Comput. Ind. Eng., 64, 631, 10.1016/j.cie.2012.12.006 Hosseinzadeh Lotfi, 2013, An improved method for ranking alternatives in multiple criteria decision analysis, Appl. Math. Model., 37, 25, 10.1016/j.apm.2011.09.074 Jahanshahloo, 2010, Ranking of units by positive ideal DMU with common weights, Expert Syst. Appl., 37, 7483, 10.1016/j.eswa.2010.04.011 Liang, 2008, Alternative secondary goals in DEA cross-efficiency evaluation, Int. J. Prod. Econ., 113, 1025, 10.1016/j.ijpe.2007.12.006 Lin, 2013, Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services, Omega, 41, 881, 10.1016/j.omega.2012.11.003 Liu, 2008, Ranking of DMUs on the DEA frontier with common weights, Comput. Oper. Res., 35, 1624, 10.1016/j.cor.2006.09.006 Llamazares, 2009, Preference aggregation and DEA: An analysis of the methods proposed to discriminate efficient candidates, European J. Oper. Res., 197, 714, 10.1016/j.ejor.2008.06.031 Noguchi, 2002, The appropriate total ranking method using DEA for multiple categorized purposes, J. Comput. Appl. Math., 146, 155, 10.1016/S0377-0427(02)00425-9 Obata, 2003, A method for discriminating efficient candidates with ranked voting data, European J. Oper. Res., 151, 233, 10.1016/S0377-2217(02)00597-0 Qin, 2010, Modeling data envelopment analysis by chance method in hybrid uncertain environments, Math. Comput. Simul., 80, 922, 10.1016/j.matcom.2009.10.005 Ramilan, 2011, Analysis of environmental and economic efficiency using a farm population micro-simulation model, Math. Comput. Simul., 81, 1344, 10.1016/j.matcom.2010.04.018 Sheikhalishahia, 2014, An integrated simulation-data envelopment analysis approach for maintenance activities planning, Int. J. Comput. Integr. Manuf., 27, 858, 10.1080/0951192X.2013.869832 Shokouhi, 2010, A robust optimization approach for imprecise data envelopment analysis, Comput. Ind. Eng., 59, 387, 10.1016/j.cie.2010.05.011 Soltanifar, 2010, Ranking of different ranking models using a voting model and its application in determining efficient candidates, Int. J. Soc. Syst. Sci., 2, 375, 10.1504/IJSSS.2010.035570 Tavana, 2011, A group AHP-TOPSIS framework for human spaceflight mission planning at NASA, Expert Systems with Applications, 38, 13588 Taylor, 2005 Wang, 2007, Discriminating DEA efficient candidates by considering their least relative total scores, J. Comput. Appl. Math., 206, 209, 10.1016/j.cam.2006.06.012 Wang, 2008, A solution method to the problem proposed by Wang in voting systems, J. Comput. Appl. Math., 221, 106, 10.1016/j.cam.2007.10.006 Wolinsky, 2002, Eliciting information from multiple experts, Games Econom. Behav., 41, 141, 10.1016/S0899-8256(02)00003-9