Document Type : Research Paper
Authors
Abstract
In this paper, a methodology is proposed to measure the efficiency of
national energy sector in IRAN. The technical and environmental
performance of the oil refineries in IRAN as a major producer of energy and
fuel are evaluated based on data from years 2010 to 2013. In this study, a
fuzzy multi-objective multi-period common weight network data
envelopment analysis approach is proposed and customized to evaluate the
performance of oil refineries. A certain scenario, called food-production in
which a refinery is assumed as a decision making unit (DMU) consuming
inputs to produce outputs, is considered to evaluate the technical and
environmental performance in presence of undesirable outputs. The main
contribution of this study are summarized as: (1) Proposing a multiobjective
common weight DEA model in order to determine the weights of
inputs and outputs in a single run; (2) Calculating the long term efficiency
scores during a multiple-periods of planning incorporating dynamic nature
of inputs and outputs; (3) Handling a compromise solution using fuzzy
mathematical programming to address multi-objective mathematical
programming; (4) Proposing a linear mathematical programming to achieve
the global optimum solutions; (5) Enhancing the discrimination power of the
DEA models; (6) Reducing the computational time of modeling and solution
procedure; (7) incorporating effective criteria in the modeling procedure.
The analysis of case study presents the efficacy and applicability of
proposed method in comparison with existing classic models.
Keywords
منابع
7136 )موسسنه مطالعنات بنین المللنی اننرژی ( -7150- ترازنامه هیدروکربوری کشور سنال 7157
"وزارت نفت معاونت برنامه ریزی و نظارت بر منابع هیدروکربوری".
7150 )وزارت نیرو(. - تراز نامه انرژی 7157
شرکت ملی پالایش وپخش فرآورده های نفتی ایران "مدیریت برنامه ریزی تلفیقنی " ، "مندیریت
هماهنگی تولید " ، "مدیریت امور منالی " ،)اطلاعنات مربنوط بنه پالایشنگاه هنا وگزارشنات سنالیانه
پالایشگاه های نفت ایران - گزارشات حسابر مستق و بازر رانونی شرکت هنا ی پنالایش سنهامی
. 7135-7150-7157- عا و خاص به انرما صورتهای مالی سال مالی منتهی به اسفند ماه 7152
Abtahi, A.R., Khalili-Damghani, K. (2011). Fuzzy data envelopment
analysis for measuring agility performance of supply chains. International
Journal of Modelling in Operations Management, 1(3), 263-288.
Al-Najjar, M., Al-Jaybajy, A. (2012). Application of Data Envelopment
Analysis to Measure the Technical Efficiency of Oil Refineries: A Case
Study. International Journal of Business Administration, 3(5), 64-77.
Jafarian-Moghaddam, A.R., Ghoseiri, K. (2011). Fuzzy dynamic
multi-objective Data Envelopment Analysis model. Expert Systems with
Applications, 38, 850–855.
Banker, R.D, Charnes, A, Cooper, W.W. (1984). Some models for
estimating technical and scale inefficiency in data envelopment analysis.
Management Science, 30, 36-51.
Charnes. A., Cooper. W.W., Rhodes, E. (1978). Measuring the
Efficiency of Decision Making Units. European Journal of Operational
Research, 2, 429-444.
Cooper, W.W., Seiford, L.M., Tone, K. (2007). Data Envelopment
Analysis: A Comprehensive text with models, applications, references
and DEA-Solver software, Springer, New York.
Chen, Y. (2005). On Preference Structure in Data Envelopment
Analysis. International Journal of Information Technology and Decision
Making, 4(3), 411-431.
Chiang, C.I., Tzeng, G.H. (2000). A multiple objective programming
approach to data envelopment analysis, In Shi, Y., Zeleny, M. (eds.),
New Frontier of Decision Making for the Information Technology Era,
World Scientific: pp. 270-285.
Dubois, D., Prade, H. (1980). Fuzzy Sets and Fuzzy Logic: Theory
and Applications. Academic press, New York.
Emrouznejad, A., Parker, B.R., Tavares, G. (2008). Evaluation of
research in efficiency and productivity: A survey and analysis of the first
30 years scholarly literature in DEA. Socio-Economic Planning
Sciences, 42, 151-157.
Farrell, M. J. (1957). The measurement of productive efficiency.
Journal of the Royal Statistical Society. Series A (General), 120 (3),
253-290.
Golany, B. (1988). An Interactive MOLP Procedure for the Extension
of DEA to Effectiveness Analysis. Journal of the Operational Research
Society, 39 (8), 725-734.
Halme, M., Korhonen, T., Salo, P., Wallenius, J. (1999). A Value
Efficiency Approach to Incorporating Preference Information in Data
Envelopment Analysis. Management Science, 45(1), 103-115.
Korhonen, T., Wallenius, J. (1998). Structural Comparison of Data
Envelopment Analysis and Multiple Objective Linear Programming.
Management Science, 44(7), 962-970.
Kaufmann, A., Gupta, M.M. (1991). Introduction to Fuzzy Arithmetic:
Theory and Applications, International Thomson Computer Press, London.
Kabnurkar, A. (2001). Mathematical modeling for data envelopment
analysis with fuzzy restrictions on weights. Doctoral Dissertation, Dep.
Of Industrial and Systems Engineering, Polytechnic Institute and State
University of Virginia.
Khalili-Damghani, K., Abtahi, A.-R. (2011). Measuring efficiency of
just in time implementation using a fuzzy data envelopment analysis
approach: real case of Iranian dairy industries. International Journal of
Advanced Operations Management, 3(3/4), 337-354.
Khalili-Damghani, K., Taghavifard, M., Olfat, L., Feizi, K. (2011). A
hybrid approach based on fuzzy DEA and simulation to measure the
efficiency of agility in supply chain: real case of dairy industry.
International Journal of Management Science and Engineering
Management, 6, 163-172.
Khalili-Damghani, K., Taghavifard, M. (2012a). 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(4), 293-317.
Khalili-Damghani, K., Taghavifard, M. (2012b). 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(2), 147-188.
Khalili-Damghani, K., Taghavifard, M., Olfat, L., Feizi, K. (2012).
Measuring agility performance in fresh food supply chains: an ordinal
two-stage data envelopment analysis. International Journal of Business
Performance and Supply Chain Modelling, 4(3/4), 206-231.
Khalili-Damghani, K., Hosseinzadeh-Lotfi, F. (2012). Performance
measurement of police traffic centres using fuzzy DEA-based Malmquist
productivity index. International Journal of Multicriteria Decision
Making, 2(1), 94-110.
Khalili-Damghani, K., Taghavifard, B. (2013). Sensitivity and
stability analysis in two-stage DEA models with fuzzy data.
International Journal of Operational Research, 17(1), 1-37.
Khalili-Damghani, K., Sadi-Nezhad, S., Hosseinzadeh-Lotfi, F.
(2014). Supply Chain Management under Fuzziness, Springer Berlin
Heidelberg, pp. 167-198.
Khalili-Damghani, K., Shahmir, Z. (2015). Uncertain network data
envelopment analysis with undesirable outputs to evaluate the efficiency
of electricity power production and distribution processes. Computers &
Industrial Engineering, 88, 131–150.
Khalili-Damghani, K., Tavana, M., Haji-Saami, E. (2015). A data
envelopment analysis model with interval data and undesirable output
for combined cycle power plant performance assessment. Expert Systems
with Applications, 42(2), 760–773.
Khalili-Damghani, K., Tavana, M., Santos-Arteaga, F.J., Mohtasham, S.
A Dynamic Multi-Stage Data Envelopment Analysis Model with Application
to Energy Consumption in the Cotton Industry. Energy Economics, In Press,
Accepted Manuscript, doi: 10.1016/j.eneco.2015.06.020.
Khalili-Damghani, K. Tavana, M. (2013). A new fuzzy network data
envelopment analysis model for measuring the performance of agility in
supply chains. International Journal of Advanced Manufacturing
Technology, 69, 291–318.
Klir, G.J., Yuan, B. (1995). Fuzzy Sets and Fuzzy Logic: Theory and
Applications, Prentice-Hall, International Inc.
Lozano, S., Villa, G. (2007). Multi objective target setting in data
envelopment analysis using AHP, Computers and Operations Research,
36, 549-564.
Lins, M.E., Meza, L.A., Silva, M.D. (2004). A multi-objective
approach to determine alternative targets in data envelopment analysis,
Journal of the Operational Research Society, 55, 1090-1101.
Li, X.B., Reeves, G.R. (1999). A multiple criteria approach to data
envelopment analysis. European Journal of Operational Researches, 115,
507-517.
Sengupta, J.K. (1995). Dynamics of Data Envelopment Analysis:
Theory of Systems Efficiency, Kluwer Academic Publishers, Dordrecht,
Netherlands
Sengupta, J.K. (1996a). Dynamics data envelopment analysis.
International Journal of Systems Science, 27, 277-284.
Sengupta, J.K. (1996b). Dynamic aspects of data envelopment
analysis. Economics Notes, 25, 143-164.
Sengupta, J.K. (1999). A dynamic efficiency model using data
envelopment analysis. International Journal of Production Economics,
62, 209-218.
Sueyoshi, T., Sekitani, K. (2005). Returns to scale in dynamic DEA.
European Journal of Operational Research, 161, 536-544.
Tavana, M., Khalili-Damghani, K. (2014). A new two-stage Stackelberg
fuzzy data envelopment analysis model. Measurement, 53, 277–296.
Tavana, M., Khalili-Damghani, K., Rahmatian, R. (2014). A hybrid
fuzzy MCDM method for measuring the performance of publicly held
pharmaceutical companies. Annals of Operations Research, 226 (1),
589-621.
Tavana, M., Khalili-Damghani, K., Sadi-Nezhad, S. (2013). A fuzzy
group data envelopment analysis model for high-technology project
selection: A case study at NASA. Computers & Industrial Engineering,
66, 10–23.
Thanassoulis, E., Dyson, R.G. (1992). Estimating preferred target
input-output levels using data envelopment analysis. European Journal
of Operational Researches, 56, 80-97.
Vijayakumar, A., Gomathi, P. (2013). Productivity Growth in Indian
Oil Refineries: Efficiency Improvement or Technical Improvement.
Journal of Humanities And Social Science, 9(2), 103-114.
Wong, B.Y.H., Luque, M., Yang, J.B. (2007). Using interactive
methods to solve DEA Problem with value judgments. Computers and
Operations Research, 36, 623-636
Yu, J.R., Tzeng, Y.C., Tzeng, G.H., Yu, T.Y., Sheu, H.J. (2004). A
Fuzzy Multiple Objective Programming To DEA With Imprecise Data.
International Journal of Uncertainty, Fuzziness and knowledge-Based
Systems, 12, (5), 591-600.
Yang, J.B., Wong, B.Y.H., Xu, D.L., Stewart, T.J. (2008). Integrated
DEA-oriented performance assessment and target setting using
interactive MOLP methods. European Journal of Operational Research,
195, 205-222.
Zhu, J. (1996). Data Envelopment Analysis with Preference Structure.
Journal of the Operational Research Society, 47, 136-150
Zimmerman, H.J. (1991). Fuzzy Set Theory and Its Applications,
second ed., Kluwer Academic Publishers, Boston
7136 )موسسنه مطالعنات بنین المللنی اننرژی ( -7150- ترازنامه هیدروکربوری کشور سنال 7157
"وزارت نفت معاونت برنامه ریزی و نظارت بر منابع هیدروکربوری".
7150 )وزارت نیرو(. - تراز نامه انرژی 7157
شرکت ملی پالایش وپخش فرآورده های نفتی ایران "مدیریت برنامه ریزی تلفیقنی " ، "مندیریت
هماهنگی تولید " ، "مدیریت امور منالی " ،)اطلاعنات مربنوط بنه پالایشنگاه هنا وگزارشنات سنالیانه
پالایشگاه های نفت ایران - گزارشات حسابر مستق و بازر رانونی شرکت هنا ی پنالایش سنهامی
. 7135-7150-7157- عا و خاص به انرما صورتهای مالی سال مالی منتهی به اسفند ماه 7152
Abtahi, A.R., Khalili-Damghani, K. (2011). Fuzzy data envelopment
analysis for measuring agility performance of supply chains. International
Journal of Modelling in Operations Management, 1(3), 263-288.
Al-Najjar, M., Al-Jaybajy, A. (2012). Application of Data Envelopment
Analysis to Measure the Technical Efficiency of Oil Refineries: A Case
Study. International Journal of Business Administration, 3(5), 64-77.
Jafarian-Moghaddam, A.R., Ghoseiri, K. (2011). Fuzzy dynamic
multi-objective Data Envelopment Analysis model. Expert Systems with
Applications, 38, 850–855.
Banker, R.D, Charnes, A, Cooper, W.W. (1984). Some models for
estimating technical and scale inefficiency in data envelopment analysis.
Management Science, 30, 36-51.
Charnes. A., Cooper. W.W., Rhodes, E. (1978). Measuring the
Efficiency of Decision Making Units. European Journal of Operational
Research, 2, 429-444.
Cooper, W.W., Seiford, L.M., Tone, K. (2007). Data Envelopment
Analysis: A Comprehensive text with models, applications, references
and DEA-Solver software, Springer, New York.
Chen, Y. (2005). On Preference Structure in Data Envelopment
Analysis. International Journal of Information Technology and Decision
Making, 4(3), 411-431.
Chiang, C.I., Tzeng, G.H. (2000). A multiple objective programming
approach to data envelopment analysis, In Shi, Y., Zeleny, M. (eds.),
New Frontier of Decision Making for the Information Technology Era,
World Scientific: pp. 270-285.
Dubois, D., Prade, H. (1980). Fuzzy Sets and Fuzzy Logic: Theory
and Applications. Academic press, New York.
Emrouznejad, A., Parker, B.R., Tavares, G. (2008). Evaluation of
research in efficiency and productivity: A survey and analysis of the first
30 years scholarly literature in DEA. Socio-Economic Planning
Sciences, 42, 151-157.
Farrell, M. J. (1957). The measurement of productive efficiency.
Journal of the Royal Statistical Society. Series A (General), 120 (3),
253-290.
Golany, B. (1988). An Interactive MOLP Procedure for the Extension
of DEA to Effectiveness Analysis. Journal of the Operational Research
Society, 39 (8), 725-734.
Halme, M., Korhonen, T., Salo, P., Wallenius, J. (1999). A Value
Efficiency Approach to Incorporating Preference Information in Data
Envelopment Analysis. Management Science, 45(1), 103-115.
Korhonen, T., Wallenius, J. (1998). Structural Comparison of Data
Envelopment Analysis and Multiple Objective Linear Programming.
Management Science, 44(7), 962-970.
Kaufmann, A., Gupta, M.M. (1991). Introduction to Fuzzy Arithmetic:
Theory and Applications, International Thomson Computer Press, London.
Kabnurkar, A. (2001). Mathematical modeling for data envelopment
analysis with fuzzy restrictions on weights. Doctoral Dissertation, Dep.
Of Industrial and Systems Engineering, Polytechnic Institute and State
University of Virginia.
Khalili-Damghani, K., Abtahi, A.-R. (2011). Measuring efficiency of
just in time implementation using a fuzzy data envelopment analysis
approach: real case of Iranian dairy industries. International Journal of
Advanced Operations Management, 3(3/4), 337-354.
Khalili-Damghani, K., Taghavifard, M., Olfat, L., Feizi, K. (2011). A
hybrid approach based on fuzzy DEA and simulation to measure the
efficiency of agility in supply chain: real case of dairy industry.
International Journal of Management Science and Engineering
Management, 6, 163-172.
Khalili-Damghani, K., Taghavifard, M. (2012a). 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(4), 293-317.
Khalili-Damghani, K., Taghavifard, M. (2012b). 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(2), 147-188.
Khalili-Damghani, K., Taghavifard, M., Olfat, L., Feizi, K. (2012).
Measuring agility performance in fresh food supply chains: an ordinal
two-stage data envelopment analysis. International Journal of Business
Performance and Supply Chain Modelling, 4(3/4), 206-231.
Khalili-Damghani, K., Hosseinzadeh-Lotfi, F. (2012). Performance
measurement of police traffic centres using fuzzy DEA-based Malmquist
productivity index. International Journal of Multicriteria Decision
Making, 2(1), 94-110.
Khalili-Damghani, K., Taghavifard, B. (2013). Sensitivity and
stability analysis in two-stage DEA models with fuzzy data.
International Journal of Operational Research, 17(1), 1-37.
Khalili-Damghani, K., Sadi-Nezhad, S., Hosseinzadeh-Lotfi, F.
(2014). Supply Chain Management under Fuzziness, Springer Berlin
Heidelberg, pp. 167-198.
Khalili-Damghani, K., Shahmir, Z. (2015). Uncertain network data
envelopment analysis with undesirable outputs to evaluate the efficiency
of electricity power production and distribution processes. Computers &
Industrial Engineering, 88, 131–150.
Khalili-Damghani, K., Tavana, M., Haji-Saami, E. (2015). A data
envelopment analysis model with interval data and undesirable output
for combined cycle power plant performance assessment. Expert Systems
with Applications, 42(2), 760–773.
Khalili-Damghani, K., Tavana, M., Santos-Arteaga, F.J., Mohtasham, S.
A Dynamic Multi-Stage Data Envelopment Analysis Model with Application
to Energy Consumption in the Cotton Industry. Energy Economics, In Press,
Accepted Manuscript, doi: 10.1016/j.eneco.2015.06.020.
Khalili-Damghani, K. Tavana, M. (2013). A new fuzzy network data
envelopment analysis model for measuring the performance of agility in
supply chains. International Journal of Advanced Manufacturing
Technology, 69, 291–318.
Klir, G.J., Yuan, B. (1995). Fuzzy Sets and Fuzzy Logic: Theory and
Applications, Prentice-Hall, International Inc.
Lozano, S., Villa, G. (2007). Multi objective target setting in data
envelopment analysis using AHP, Computers and Operations Research,
36, 549-564.
Lins, M.E., Meza, L.A., Silva, M.D. (2004). A multi-objective
approach to determine alternative targets in data envelopment analysis,
Journal of the Operational Research Society, 55, 1090-1101.
Li, X.B., Reeves, G.R. (1999). A multiple criteria approach to data
envelopment analysis. European Journal of Operational Researches, 115,
507-517.
Sengupta, J.K. (1995). Dynamics of Data Envelopment Analysis:
Theory of Systems Efficiency, Kluwer Academic Publishers, Dordrecht,
Netherlands
Sengupta, J.K. (1996a). Dynamics data envelopment analysis.
International Journal of Systems Science, 27, 277-284.
Sengupta, J.K. (1996b). Dynamic aspects of data envelopment
analysis. Economics Notes, 25, 143-164.
Sengupta, J.K. (1999). A dynamic efficiency model using data
envelopment analysis. International Journal of Production Economics,
62, 209-218.
Sueyoshi, T., Sekitani, K. (2005). Returns to scale in dynamic DEA.
European Journal of Operational Research, 161, 536-544.
Tavana, M., Khalili-Damghani, K. (2014). A new two-stage Stackelberg
fuzzy data envelopment analysis model. Measurement, 53, 277–296.
Tavana, M., Khalili-Damghani, K., Rahmatian, R. (2014). A hybrid
fuzzy MCDM method for measuring the performance of publicly held
pharmaceutical companies. Annals of Operations Research, 226 (1),
589-621.
Tavana, M., Khalili-Damghani, K., Sadi-Nezhad, S. (2013). A fuzzy
group data envelopment analysis model for high-technology project
selection: A case study at NASA. Computers & Industrial Engineering,
66, 10–23.
Thanassoulis, E., Dyson, R.G. (1992). Estimating preferred target
input-output levels using data envelopment analysis. European Journal
of Operational Researches, 56, 80-97.
Vijayakumar, A., Gomathi, P. (2013). Productivity Growth in Indian
Oil Refineries: Efficiency Improvement or Technical Improvement.
Journal of Humanities And Social Science, 9(2), 103-114.
Wong, B.Y.H., Luque, M., Yang, J.B. (2007). Using interactive
methods to solve DEA Problem with value judgments. Computers and
Operations Research, 36, 623-636
Yu, J.R., Tzeng, Y.C., Tzeng, G.H., Yu, T.Y., Sheu, H.J. (2004). A
Fuzzy Multiple Objective Programming To DEA With Imprecise Data.
International Journal of Uncertainty, Fuzziness and knowledge-Based
Systems, 12, (5), 591-600.
Yang, J.B., Wong, B.Y.H., Xu, D.L., Stewart, T.J. (2008). Integrated
DEA-oriented performance assessment and target setting using
interactive MOLP methods. European Journal of Operational Research,
195, 205-222.
Zhu, J. (1996). Data Envelopment Analysis with Preference Structure.
Journal of the Operational Research Society, 47, 136-150
Zimmerman, H.J. (1991). Fuzzy Set Theory and Its Applications,
second ed., Kluwer Academic Publishers, Boston
)