Pendekatan Berdasarkan Skenario Untuk Meranking Unit Pengambilan Keputusan (UPK) Dalam Model Stochastic Data Envelopment Analysis (SDEA)
DAFTAR PUSTAKA
Allen, F., Broswell, M., Rao, P.V., 1972. Distribution free approximations for
chance constraints. Operations Research 22, 610-621.
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in
data envelopment analysis. Management Science, 39, 1261-1264.
Banker, R., A. Charnes and W.W. Cooper, 1984. Some models for estimating
technical and scale inefficiencies in data envelopment analysis, Management
Science 30, 1078-1092.
Charnes, A. and Cooper, W.W., 1959, Chance-constrained programming. Manage.
Sci., 6, 7379.
Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision
making units. European Journal of Operational Research 2, 429-444.
Charnes, A., Cooper, W.W., Rhodes, E., 1981. Evaluating program and managerial
efficiency: An application of data envelopment analysis to program follow
through. Management Science 27, 668-697.
Charnes, A., Cooper, W.W., Symonds, G.H., 1958. Cost horizons and certainty
equivalents: An approach to stochastic programming of heating oil. Management Science 4, 235-263.
Charnes, A., Cooper, W.W., Thrall, R.M., 1991. A structure for classifying and
characterizing efficiencies and inefficiencies in data envelopment analysis.
Journal of Productivity Analysis 2, 197-237.
Charnes, A., Cooper, W.W., Thrall, R.M., 1986. Identifying and classifying efficiencies and inefficiencies in data envelopment analysis. Operations Research
Letters 5, 105-116.
Charnes, A., Haag, S., Jaska, P., Semple, J., 1992. Sensitivity of efficiency classifications in the additive model of data envelopment analysis. International
Journal of Systems Science 23, 789-798.
Charnes, A., Neralic, L., 1990. Sensitivity analysis of the additive model in data
envelopment analysis. European Journal of Operational Research 48, 332-341.
Cooper, W.W., Park, K.S. and Yu, G., 1999. IDEA and AR-IDEA: models for
dealing with imprecise data in DEA. Manage. Sci., 45, 597607.
Cooper, W.W., Gu, B., Li, S., 2001. Note: Alternative treatments of congestion A response to the Cherchye, Kuosmanen and Post critique. European Journal
of Operational Research 132, 85-87.
Cooper, W.W., Deng, H., Gu, B., Li, S., Thrall, R.M., 2001. Using DEA to
improve the management of congestion in Chinese industries (1981?1997).
Socio-Economic Planning Sciences 35, 1-16.
Cooper, W.W., H. Deng, Z. Huang and S. Li (2001a). A Chance Constrained Programming Approach to Congestion in Stochastic Data Envelopment Analysis,.European Journal of Operational Research (submitted).
109
Universitas Sumatera Utara
110
Cooper, W.W., Li, S., Seiford, L.M., Tone, K., Thrall, R.M., Zhu, J., 2001. Sensitivity and stability analysis in DEA: Some recent developments. Journal of
Productivity Analysis 15, 217-246.
Cooper, W.W., Deng, H., Huang, Z.M., Li, S.X., 2002. Change constrined programming approaches to technical efficiencies and inefficiencies in stochastic
data envelopment analysis. Journal of the Operational Research Society 53,
1347-1356.
Cooper, W.W., Deng, H., Huang, Z.M., Li, S.X., 2002. A one model approach to
congestion in data envelopment analysis. Socio-Economic Planning Sciences
36, 231-238.
Cooper, W.W., Huang, Z., Li, S., 1996a. Satisficing DEA models under chance
constraints. The Annals of Operations Research 66, 279-295.
Cooper, W.W., Thompson, R.G., Thrall, R.M., 1996b. Introduction: Ex3180 F.
Hosseinzadeh Lotfi et al tensions and new developments in DEA. The Annals
of Operations Research 66, 3-46.
C. Yao, 2003. Measuring super-efficiency in DEA in presence of infeasibility, European Journal of Operational research, 161- 2, 429444.
Doyle, J. and Green, R., 1993. Data envelopment analysis and multiple criteria
decision making. Omega, 21, 713715.
Farrell, M.J. 1957. The Measurement of Productive Efficiency. Journal of the Royal
Statistical Society A 120, part 3: pp. 253-281.
Fried H. O., Knox Lovell C. A. and Schmid S. S. , 1993. The Measurement of
Productive Efficiency: Techniques and Applications with OUP. Oxford University Press.
Huang, Z. and Li S. X., 2001. Chance constrained programming and stochastic
DEA models. School of Business, Adelphi University, Garden City, New York.
Land, K.C, C.A.K Lovell, and S. Thore, 1993. Chance-Constrained data envelopment analysis. Managerial and Decision Economics, 14, 541-554.
L.M. Seiford and J. Zhu, 1998. Stability regions for maintaining efficiency in data
envelopment analysis, European Journal of Operational Research, 108, 12739.
Markowitz, Harry, 1952. Portfolio selection. J. Financ. 7, 7797
Moskowitz, Herbert., Tang, J. and Lam, P., 2000. Distribution of aggregate utility
using stochastic elements of additive multiattribute utility models. Decision
Sci., 31, 327-360.
Olesen, O. B., 2002. Comparing and combining two approaches for chance constrained DEA, Technical Report, The University of Southern Denmark.
Olesen, O. B. and N.C. Petersen, 1995. Chance Constrained efficiency evaluation.
Management Science, 41, 442-457.
Pagnoncelli B.K., Ahmed S., Shapiro A., 2009. Sample Average Approximation
Method for Chance Constrained Programming: Theory and Applications,
Springer Science, 142: 399416.
Universitas Sumatera Utara
111
R.M. Thrall, 1996. Duality, classification and slack in data envelopment analysis,
Annals of Operational research, 66, 109-138.
Shapiro, A., 2003. Monte Carlo sampling methods. In: Ruszczynski, A., Shapiro,
A. (eds.) Stochastic Programming. Handbooks in OR & MS, vol. 10, pp.
353425. North-Holland, Amsterdam
Sexton, T.R. and Silkman, R.H., 1986. Data envelopment analysis: critique and
extensions. In Measuring Efficiency: An Assessment of Data Envelopment
Analysis, edited by R.H. Silkman, (Jossey-Bass: San Francisco).
Saen R. F. 2010. Developing a new data envelopment analysis methodology for
supplier selection in the presence of both undesirable outputs and imprecise
data. International Journal of Advanced Manufacturing Technology Vol. 51,
p.1243-1250.
Seiford, L.M and Zhu J., 1998. Stability regions for maintaining efficiency in data
envelopment analysis, European Journal of Operational Research, 108, 12739.
Seiford, L.M., Zhu, J., 1999. Infeasibility of super-efficiency data envelopment analysis. INFOR 37, 174187.
Sexton, T.R. and Silkman, R.H., 1986. Data envelopment analysis: critique and
extensions. In Measuring Efficiency: An Assessment of Data Envelopment
Analysis, edited by R.H. Silkman, (Jossey-Bass: San Francisco).
Tim ICT Pura, 2012, Indeks TIK 165 Kabupaten/Kota Indonesia, Buku 2 ICT
Pura.
Vercellis, C., 2009. Business Intelligence: Data Mining and Optimization for Decision Making, John Wiey & Sons, Ltd.
Vielma J.P., Ahmed S., and Nemhauser G.L., 2012. Mixed integer linear programming formulations for probabilistic constraints, to appear in operations
research letters (preprint).
William W. Cooper, H. Deng, Zhimin Huang, Sus X.Li, 2003. Chance Constrained
programming approaches to congestion in stochastic data envelopment analysis. European Journal of Operational Research.
Wu, T. & Blackhurst, J. 2009. Supplier Evaluation and Selection Augmented DEA
Approach. International Journal of Production Research, 47(16), 4593-4608.
Wu D. and Olson D. L., 2006. A comparison of stochastic dominance and stochastic
DEA for vendor evaluation. -gInternational journal of production research,
46, 2313-2327.
Zhu, J. 2001. Super-efficiency and DEA sensitivity analysis, European Journal of
Operational Research, 129, 443-455.
Universitas Sumatera Utara
Allen, F., Broswell, M., Rao, P.V., 1972. Distribution free approximations for
chance constraints. Operations Research 22, 610-621.
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in
data envelopment analysis. Management Science, 39, 1261-1264.
Banker, R., A. Charnes and W.W. Cooper, 1984. Some models for estimating
technical and scale inefficiencies in data envelopment analysis, Management
Science 30, 1078-1092.
Charnes, A. and Cooper, W.W., 1959, Chance-constrained programming. Manage.
Sci., 6, 7379.
Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision
making units. European Journal of Operational Research 2, 429-444.
Charnes, A., Cooper, W.W., Rhodes, E., 1981. Evaluating program and managerial
efficiency: An application of data envelopment analysis to program follow
through. Management Science 27, 668-697.
Charnes, A., Cooper, W.W., Symonds, G.H., 1958. Cost horizons and certainty
equivalents: An approach to stochastic programming of heating oil. Management Science 4, 235-263.
Charnes, A., Cooper, W.W., Thrall, R.M., 1991. A structure for classifying and
characterizing efficiencies and inefficiencies in data envelopment analysis.
Journal of Productivity Analysis 2, 197-237.
Charnes, A., Cooper, W.W., Thrall, R.M., 1986. Identifying and classifying efficiencies and inefficiencies in data envelopment analysis. Operations Research
Letters 5, 105-116.
Charnes, A., Haag, S., Jaska, P., Semple, J., 1992. Sensitivity of efficiency classifications in the additive model of data envelopment analysis. International
Journal of Systems Science 23, 789-798.
Charnes, A., Neralic, L., 1990. Sensitivity analysis of the additive model in data
envelopment analysis. European Journal of Operational Research 48, 332-341.
Cooper, W.W., Park, K.S. and Yu, G., 1999. IDEA and AR-IDEA: models for
dealing with imprecise data in DEA. Manage. Sci., 45, 597607.
Cooper, W.W., Gu, B., Li, S., 2001. Note: Alternative treatments of congestion A response to the Cherchye, Kuosmanen and Post critique. European Journal
of Operational Research 132, 85-87.
Cooper, W.W., Deng, H., Gu, B., Li, S., Thrall, R.M., 2001. Using DEA to
improve the management of congestion in Chinese industries (1981?1997).
Socio-Economic Planning Sciences 35, 1-16.
Cooper, W.W., H. Deng, Z. Huang and S. Li (2001a). A Chance Constrained Programming Approach to Congestion in Stochastic Data Envelopment Analysis,.European Journal of Operational Research (submitted).
109
Universitas Sumatera Utara
110
Cooper, W.W., Li, S., Seiford, L.M., Tone, K., Thrall, R.M., Zhu, J., 2001. Sensitivity and stability analysis in DEA: Some recent developments. Journal of
Productivity Analysis 15, 217-246.
Cooper, W.W., Deng, H., Huang, Z.M., Li, S.X., 2002. Change constrined programming approaches to technical efficiencies and inefficiencies in stochastic
data envelopment analysis. Journal of the Operational Research Society 53,
1347-1356.
Cooper, W.W., Deng, H., Huang, Z.M., Li, S.X., 2002. A one model approach to
congestion in data envelopment analysis. Socio-Economic Planning Sciences
36, 231-238.
Cooper, W.W., Huang, Z., Li, S., 1996a. Satisficing DEA models under chance
constraints. The Annals of Operations Research 66, 279-295.
Cooper, W.W., Thompson, R.G., Thrall, R.M., 1996b. Introduction: Ex3180 F.
Hosseinzadeh Lotfi et al tensions and new developments in DEA. The Annals
of Operations Research 66, 3-46.
C. Yao, 2003. Measuring super-efficiency in DEA in presence of infeasibility, European Journal of Operational research, 161- 2, 429444.
Doyle, J. and Green, R., 1993. Data envelopment analysis and multiple criteria
decision making. Omega, 21, 713715.
Farrell, M.J. 1957. The Measurement of Productive Efficiency. Journal of the Royal
Statistical Society A 120, part 3: pp. 253-281.
Fried H. O., Knox Lovell C. A. and Schmid S. S. , 1993. The Measurement of
Productive Efficiency: Techniques and Applications with OUP. Oxford University Press.
Huang, Z. and Li S. X., 2001. Chance constrained programming and stochastic
DEA models. School of Business, Adelphi University, Garden City, New York.
Land, K.C, C.A.K Lovell, and S. Thore, 1993. Chance-Constrained data envelopment analysis. Managerial and Decision Economics, 14, 541-554.
L.M. Seiford and J. Zhu, 1998. Stability regions for maintaining efficiency in data
envelopment analysis, European Journal of Operational Research, 108, 12739.
Markowitz, Harry, 1952. Portfolio selection. J. Financ. 7, 7797
Moskowitz, Herbert., Tang, J. and Lam, P., 2000. Distribution of aggregate utility
using stochastic elements of additive multiattribute utility models. Decision
Sci., 31, 327-360.
Olesen, O. B., 2002. Comparing and combining two approaches for chance constrained DEA, Technical Report, The University of Southern Denmark.
Olesen, O. B. and N.C. Petersen, 1995. Chance Constrained efficiency evaluation.
Management Science, 41, 442-457.
Pagnoncelli B.K., Ahmed S., Shapiro A., 2009. Sample Average Approximation
Method for Chance Constrained Programming: Theory and Applications,
Springer Science, 142: 399416.
Universitas Sumatera Utara
111
R.M. Thrall, 1996. Duality, classification and slack in data envelopment analysis,
Annals of Operational research, 66, 109-138.
Shapiro, A., 2003. Monte Carlo sampling methods. In: Ruszczynski, A., Shapiro,
A. (eds.) Stochastic Programming. Handbooks in OR & MS, vol. 10, pp.
353425. North-Holland, Amsterdam
Sexton, T.R. and Silkman, R.H., 1986. Data envelopment analysis: critique and
extensions. In Measuring Efficiency: An Assessment of Data Envelopment
Analysis, edited by R.H. Silkman, (Jossey-Bass: San Francisco).
Saen R. F. 2010. Developing a new data envelopment analysis methodology for
supplier selection in the presence of both undesirable outputs and imprecise
data. International Journal of Advanced Manufacturing Technology Vol. 51,
p.1243-1250.
Seiford, L.M and Zhu J., 1998. Stability regions for maintaining efficiency in data
envelopment analysis, European Journal of Operational Research, 108, 12739.
Seiford, L.M., Zhu, J., 1999. Infeasibility of super-efficiency data envelopment analysis. INFOR 37, 174187.
Sexton, T.R. and Silkman, R.H., 1986. Data envelopment analysis: critique and
extensions. In Measuring Efficiency: An Assessment of Data Envelopment
Analysis, edited by R.H. Silkman, (Jossey-Bass: San Francisco).
Tim ICT Pura, 2012, Indeks TIK 165 Kabupaten/Kota Indonesia, Buku 2 ICT
Pura.
Vercellis, C., 2009. Business Intelligence: Data Mining and Optimization for Decision Making, John Wiey & Sons, Ltd.
Vielma J.P., Ahmed S., and Nemhauser G.L., 2012. Mixed integer linear programming formulations for probabilistic constraints, to appear in operations
research letters (preprint).
William W. Cooper, H. Deng, Zhimin Huang, Sus X.Li, 2003. Chance Constrained
programming approaches to congestion in stochastic data envelopment analysis. European Journal of Operational Research.
Wu, T. & Blackhurst, J. 2009. Supplier Evaluation and Selection Augmented DEA
Approach. International Journal of Production Research, 47(16), 4593-4608.
Wu D. and Olson D. L., 2006. A comparison of stochastic dominance and stochastic
DEA for vendor evaluation. -gInternational journal of production research,
46, 2313-2327.
Zhu, J. 2001. Super-efficiency and DEA sensitivity analysis, European Journal of
Operational Research, 129, 443-455.
Universitas Sumatera Utara