How to cite this paper
Sameie, H & Arvan, M. (2015). A simulation-based Data Envelopment Analysis (DEA) model to evaluate wind plants locations.Decision Science Letters , 4(2), 165-180.
Refrences
Abdollahi, M., Arvan, M., Omidvar, A., & Ameri, F. (2014). A simulation optimization approach to apply value at risk analysis on the inventory routing problem with backlogged demand. International Journal of Industrial Engineering Computations, 5, 603–620.
Abdollahi, M., Arvan, M., & Razmi, J. (2014). An integrated approach for Supplier Portfolio Selection: Lean or Agile? Expert Systems with Applications, 42(1), 679-690
Al-Eraqi, A. S., Barros, C. P., Mustaffa, A., & Khader, A. T. (2007). Evaluating the Location Efficiency of Arabian and African Seaports Using Data Envelopment Analysis (DEA).
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management science, 39(10), 1261-1264.
Andor, M., & Hesse, F. (2011). A Monte Carlo Simulation comparing DEA, SFA and two simple approaches to combine efficiency estimates: CAWM discussion paper/Centrum für Angewandte Wirtschaftsforschung Münster.
Aras, H., Erdo?mu?, ?., & Koç, E. (2004). Multi-criteria selection for a wind observation station location using analytic hierarchy process. Renewable Energy, 29(8), 1383-1392.
Arvan, M., Tavakkoli-Moghaddam, R., & Abdollahi, M. (2014). Designing a bi-objective and multi-product supply chain network for the supply of blood. Uncertain Supply Chain Management, 3(1), 57-68.
Aytun Ozturk, U., & Norman, B. A. (2004). Heuristic methods for wind energy conversion system positioning. Electric Power Systems Research, 70(3), 179-185.
Azadeh, A., Ghaderi, S., & Maghsoudi, A. (2008). Location optimization of solar plants by an integrated hierarchical DEA PCA approach. Energy Policy, 36(10), 3993-4004.
Azadeh, A., Ghaderi, S., & Nasrollahi, M. (2011). Location optimization of wind plants in Iran by an integrated hierarchical Data Envelopment Analysis. Renewable Energy, 36(5), 1621-1631.
Bhatnagar, R., & Sohal, A. S. (2005). Supply chain competitiveness: measuring the impact of location factors, uncertainty and manufacturing practices. Technovation, 25(5), 443-456.
Billinton, R., & Bai, G. (2004). Generating capacity adequacy associated with wind energy. Energy Conversion, IEEE Transactions on, 19(3), 641-646.
Bossel, H. (1994). Modeling and simulation: AK Peters Wellesley, MA.
Bowling, I. M., Ponce-Ortega, J. M. a., & El-Halwagi, M. M. (2011). Facility location and supply chain optimization for a biorefinery. Industrial & Engineering Chemistry Research, 50(10), 6276-6286.
Celik, A. N. (2004). A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey. Renewable Energy, 29(4), 593-604.
Charnes, A. (1994). Data envelopment analysis: theory, methodology, and application: Kluwer Academic Pub.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Chatterjee, N., & Bose, G. (2013). A COPRAS-F base multi-criteria group decision making approach for site selection of wind farm. Decision Science Letters, 2(1), 1-10.
Cooper, W. W. (2011). Handbook on data envelopment analysis: Springer Science+ Business Media.
Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Data envelopment analysis: History, models, and interpretations: Springer.
Davis, R. S. (1992). Equation for the determination of the density of moist air (1981/91). Metrologia, 29(1), 67-70.
Dorvlo, A. S. (2002). Estimating wind speed distribution. Energy Conversion and Management, 43(17), 2311-2318.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
Ganley, J. A., & Cubbin, J. S. (1992). Public sector efficiency measurement: Applications of data envelopment analysis: Elsevier Science Inc.
Gendron, B., Khuong, P.-V., & Semet, F. (2013). A Lagrangian-Based Branch-and-Bound Algorithm for the Two-Level Uncapacitated Facility Location Problem with Single-Assignment Constraints: Technical Report 2013-21, CIRRELT.
Gollowitzer, S., & Ljubi?, I. (2011). MIP models for connected facility location: A theoretical and computational study. Computers & Operations Research, 38(2), 435-449.
Grogg, K. (2005). Harvesting the Wind: The Physics of Wind Turbines.
Guo, P. (2009). Fuzzy data envelopment analysis and its application to location problems. Information Sciences, 179(6), 820-829.
Klimberg, R. K., & Ratick, S. J. (2008). Modeling data envelopment analysis (DEA) efficient location/allocation decisions. Computers & Operations Research, 35(2), 457-474.
Mar?n, A. (2011). The discrete facility location problem with balanced allocation of customers. European Journal of Operational Research, 210(1), 27-38.
McMullen, P. R., & Frazier, G. V. (1999). Using simulation and data envelopment analysis to compare assembly line balancing solutions. Journal of Productivity Analysis, 11(2), 149-168.
Mitropoulos, P., Mitropoulos, I., & Giannikos, I. (2012). Combining DEA with location analysis for the effective consolidation of services in the health sector. Computers & Operations Research, 40(9), 2241-2250.
Mujumdar, A. (1996). Techniques and Topics in Flow Measurement. Drying Technology, 14(7-8), 1909-1910.
Rentizelas, A., Tatsiopoulos, I., & Tolis, A. (2009). An optimization model for multi-biomass tri-generation energy supply. Biomass and bioenergy, 33(2), 223-233.
Robinson, S. (2004). Simulation: the practice of model development and use: Wiley.
Seguro, J., & Lambert, T. (2000). Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis. Journal of Wind Engineering and Industrial Aerodynamics, 85(1), 75-84.
Talluri, S. (2000). Data envelopment analysis: models and extensions. Decision Line, 31(3), 8-11.
Wang, C., & Nehrir, M. H. (2008). Power management of a stand-alone wind/photovoltaic/fuel cell energy system. Energy Conversion, IEEE Transactions on, 23(3), 957-967.
Abdollahi, M., Arvan, M., & Razmi, J. (2014). An integrated approach for Supplier Portfolio Selection: Lean or Agile? Expert Systems with Applications, 42(1), 679-690
Al-Eraqi, A. S., Barros, C. P., Mustaffa, A., & Khader, A. T. (2007). Evaluating the Location Efficiency of Arabian and African Seaports Using Data Envelopment Analysis (DEA).
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management science, 39(10), 1261-1264.
Andor, M., & Hesse, F. (2011). A Monte Carlo Simulation comparing DEA, SFA and two simple approaches to combine efficiency estimates: CAWM discussion paper/Centrum für Angewandte Wirtschaftsforschung Münster.
Aras, H., Erdo?mu?, ?., & Koç, E. (2004). Multi-criteria selection for a wind observation station location using analytic hierarchy process. Renewable Energy, 29(8), 1383-1392.
Arvan, M., Tavakkoli-Moghaddam, R., & Abdollahi, M. (2014). Designing a bi-objective and multi-product supply chain network for the supply of blood. Uncertain Supply Chain Management, 3(1), 57-68.
Aytun Ozturk, U., & Norman, B. A. (2004). Heuristic methods for wind energy conversion system positioning. Electric Power Systems Research, 70(3), 179-185.
Azadeh, A., Ghaderi, S., & Maghsoudi, A. (2008). Location optimization of solar plants by an integrated hierarchical DEA PCA approach. Energy Policy, 36(10), 3993-4004.
Azadeh, A., Ghaderi, S., & Nasrollahi, M. (2011). Location optimization of wind plants in Iran by an integrated hierarchical Data Envelopment Analysis. Renewable Energy, 36(5), 1621-1631.
Bhatnagar, R., & Sohal, A. S. (2005). Supply chain competitiveness: measuring the impact of location factors, uncertainty and manufacturing practices. Technovation, 25(5), 443-456.
Billinton, R., & Bai, G. (2004). Generating capacity adequacy associated with wind energy. Energy Conversion, IEEE Transactions on, 19(3), 641-646.
Bossel, H. (1994). Modeling and simulation: AK Peters Wellesley, MA.
Bowling, I. M., Ponce-Ortega, J. M. a., & El-Halwagi, M. M. (2011). Facility location and supply chain optimization for a biorefinery. Industrial & Engineering Chemistry Research, 50(10), 6276-6286.
Celik, A. N. (2004). A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey. Renewable Energy, 29(4), 593-604.
Charnes, A. (1994). Data envelopment analysis: theory, methodology, and application: Kluwer Academic Pub.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Chatterjee, N., & Bose, G. (2013). A COPRAS-F base multi-criteria group decision making approach for site selection of wind farm. Decision Science Letters, 2(1), 1-10.
Cooper, W. W. (2011). Handbook on data envelopment analysis: Springer Science+ Business Media.
Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Data envelopment analysis: History, models, and interpretations: Springer.
Davis, R. S. (1992). Equation for the determination of the density of moist air (1981/91). Metrologia, 29(1), 67-70.
Dorvlo, A. S. (2002). Estimating wind speed distribution. Energy Conversion and Management, 43(17), 2311-2318.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
Ganley, J. A., & Cubbin, J. S. (1992). Public sector efficiency measurement: Applications of data envelopment analysis: Elsevier Science Inc.
Gendron, B., Khuong, P.-V., & Semet, F. (2013). A Lagrangian-Based Branch-and-Bound Algorithm for the Two-Level Uncapacitated Facility Location Problem with Single-Assignment Constraints: Technical Report 2013-21, CIRRELT.
Gollowitzer, S., & Ljubi?, I. (2011). MIP models for connected facility location: A theoretical and computational study. Computers & Operations Research, 38(2), 435-449.
Grogg, K. (2005). Harvesting the Wind: The Physics of Wind Turbines.
Guo, P. (2009). Fuzzy data envelopment analysis and its application to location problems. Information Sciences, 179(6), 820-829.
Klimberg, R. K., & Ratick, S. J. (2008). Modeling data envelopment analysis (DEA) efficient location/allocation decisions. Computers & Operations Research, 35(2), 457-474.
Mar?n, A. (2011). The discrete facility location problem with balanced allocation of customers. European Journal of Operational Research, 210(1), 27-38.
McMullen, P. R., & Frazier, G. V. (1999). Using simulation and data envelopment analysis to compare assembly line balancing solutions. Journal of Productivity Analysis, 11(2), 149-168.
Mitropoulos, P., Mitropoulos, I., & Giannikos, I. (2012). Combining DEA with location analysis for the effective consolidation of services in the health sector. Computers & Operations Research, 40(9), 2241-2250.
Mujumdar, A. (1996). Techniques and Topics in Flow Measurement. Drying Technology, 14(7-8), 1909-1910.
Rentizelas, A., Tatsiopoulos, I., & Tolis, A. (2009). An optimization model for multi-biomass tri-generation energy supply. Biomass and bioenergy, 33(2), 223-233.
Robinson, S. (2004). Simulation: the practice of model development and use: Wiley.
Seguro, J., & Lambert, T. (2000). Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis. Journal of Wind Engineering and Industrial Aerodynamics, 85(1), 75-84.
Talluri, S. (2000). Data envelopment analysis: models and extensions. Decision Line, 31(3), 8-11.
Wang, C., & Nehrir, M. H. (2008). Power management of a stand-alone wind/photovoltaic/fuel cell energy system. Energy Conversion, IEEE Transactions on, 23(3), 957-967.