Prof. Reza Farzipoor Saen
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Prof. Reza Farzipoor Saen

Professor
Islamic Azad University, Iran

Highest Degree
Ph.D. in Industrial Management from Islamic Azad University, Parand, Iran

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Biography

Dr. Reza Farzipoor Saen is working as Faculty member of Management and Accounting, Islamic Azad University, Karaj Branch, Karaj, Iran. He obtained his Ph.D. in Industrial Management from Islamic Azad University, Iran. His area of expertise includes Operations Research/Management Science, Supply Chain Management, Operations Management, and Productivity Management (Data Envelopment Analysis). He has 96 publications in journals contributed as author/co-author.

Area of Interest:

Business Management and Accounting
100%
Industrial Management
62%
Operations Research
90%
Data Envelopment Analysis
75%
Supply Chain Management
55%

Research Publications in Numbers

Books
0
Chapters
4
Articles
221
Abstracts
0

Selected Publications

  1. Tavassoli, M. and R.F. Saen, 2019. Predicting group membership of sustainable suppliers via data envelopment analysis and discriminant analysis. Sustain. Prod. Consumpt., 18: 41-52.
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  2. Shabanpour, H., A. Fathi, S. Yousefi and R.F. Saen, 2019. Ranking sustainable suppliers using congestion approach of data envelopment analysis. J. Cleaner Prod., Vol. 240. 10.1016/j.jclepro.2019.118190.
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  3. Momeni, E., F.H. Lotfi, R.F. Saen and E. Najafi, 2019. Centralized DEA-based reallocation of emission permits under cap and trade regulation. J. Cleaner Prod., 234: 306-314.
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  4. Mavi, R.K., R.F. Saen and M. Goh, 2019. Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach. Technol. Forecasting Social Change, 144: 553-562.
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  5. Mavi, R.K., A. Fathi, R.F. Saen and N.K. Mavi, 2019. Eco-innovation in transportation industry: A double frontier common weights analysis with ideal point method for Malmquist productivity index. Resour. Conserv. Recycl., 147: 39-48.
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  6. Kalantary, M. and R.F. Saen, 2019. Assessing sustainability of supply chains: An inverse network dynamic DEA model. Comput. Ind. Eng., 135: 1224-1238.
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  7. Izadikhah, M., M. Azadi, V.S. Kahi and R.F. Saen, 2019. Developing a new chance constrained NDEA model to measure the performance of humanitarian supply chains. Int. J. Prod. Res., 57: 662-682.
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  8. Izadikhah, M. and R.F. Saen, 2019. Solving voting system by data envelopment analysis for assessing sustainability of suppliers. Group Decis. Negotiation, 28: 641-669.
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  9. Zoroofchi, K.H., R.F. Saen, P.B. Lari and M. Azadi, 2018. A combination of range-adjusted measure, cross-efficiency and assurance region for assessing sustainability of suppliers in the presence of undesirable factors. Int. J. Ind. Syst. Eng., 29: 163-176.
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  10. Tavana, M., M. Izadikhah, D. Di Caprio and R. Farzipoor Saen, 2018. A new dynamic range directional measure for two-stage data envelopment analysis models with negative data. Comput. Ind. Eng., 115: 427-448.
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  11. Rashidi, K. and R.F. Saen, 2018. Incorporating dynamic concept into gradual efficiency: Improving suppliers in sustainable supplier development. J. Cleaner Prod., 202: 226-243.
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  12. Moshtaghi, H.R., G.R. Faramarzi and R.F. Saen, 2018. Developing new methods for determining weights of components in network data envelopment analysis. Int. J. Operat. Res., 32: 223-250.
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  13. Mahdiloo, M., M. Toloo, T.T. Duong, R. Farzipoor Saen and P. Tatham, 2018. Integrated data envelopment analysis: Linear vs. nonlinear model. Eur. J. Operat. Res., 268: 255-267.
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  14. Mahdiloo, M., A.H. Jafarzadeh, R.F. Saen, Y. Wu and J. Rice, 2018. Modelling undesirable outputs in multiple objective data envelopment analysis. J. Operat. Res. Soc., 69: 1903-1919.
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  15. Kalantary, M., R.F. Saen and A.T. Eshlaghy, 2018. Sustainability assessment of supply chains by inverse network dynamic data envelopment analysis. Sci. Iran. Trans. E: Ind. Eng., 25: 3723-3743.
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  16. Izadikhah, M., R.F. Saen and R. Roostaee, 2018. How to assess sustainability of suppliers in the presence of volume discount and negative data in data envelopment analysis? Ann. Operat. Res., 269: 241-267.
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  17. Izadikhah, M. and R.F. Saen, 2018. Assessing sustainability of supply chains by chance-constrained two-stage DEA model in the presence of undesirable factors. Comput. Operat. Res., 100: 343-367.
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  18. Hassanzadeh, A., S. Yousefi, R. Farzipoor Saen and S.S.S. Hosseininia, 2018. How to assess sustainability of countries via inverse data envelopment analysis? Clean Technol. Environ. Policy, 20: 29-40.
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  19. Fathi, A. and R. Farzipoor Saen, 2018. A novel bidirectional network data envelopment analysis model for evaluating sustainability of distributive supply chains of transport companies. J. Cleaner Prod., 184: 696-708.
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  20. Boudaghi, E. and R. Farzipoor Saen, 2018. Developing a novel model of data envelopment analysis-discriminant analysis for predicting group membership of suppliers in sustainable supply chain. Comput. Operat. Res., 89: 348-359.
    CrossRef  |  Direct Link  |  
  21. Badiezadeh, T., R.F. Saen and T. Samavati, 2018. Assessing sustainability of supply chains by double frontier network DEA: A big data approach. Comput. Operat. Res., 98: 284-290.
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  22. Azizi, H., A. Amirteimoori and R. Farzipoor Saen, 2018. Supplier selection based on optimistic and pessimistic approaches. J. Dev. Evol. Manage., 31: 11-20, (In Persian).
  23. Ahranjani, L.Z., R.K. Matin and R.F. Saen, 2018. Economies of scope in two-stage production systems: A data envelopment analysis approach. RAIRO-Operat. Res., 52: 335-349.
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  24. Yousefi, S., R. Soltani, R.F. Saen and M.S. Pishvaee, 2017. A robust fuzzy possibilistic programming for a new network GP-DEA model to evaluate sustainable supply chains. J. Cleaner Prod., 166: 537-549.
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  25. Tavassoli, M., T. Badizadeh and R. Farzipoor Saen, 2017. A joint measurement of efficiency and effectiveness for ranking power distribution units in Iran: Integrated data envelopment analysis approach. Int. J. Inform. Decis. Sci., 9: 353-368.
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  26. Tavana, M., H. Shabanpour, S. Yousefi and R. Farzipoor Saen, 2017. A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation. Neural Comput. Applic., 28: 3683-3696.
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  27. Shokri Kahi, V., S. Yousefi, H. Shabanpour and R. Farzipoor Saen, 2017. How to evaluate sustainability of supply chains? A dynamic network DEA approach. Ind. Manage. Data Syst., 117: 1866-1889.
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  28. Shabanpour, H., S. Yousefi and R.F. Saen, 2017. Future planning for benchmarking and ranking sustainable suppliers using goal programming and robust double frontiers DEA. Transport. Res. Part D: Transport Environ., 50: 129-143.
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  29. Shabanpour, H., S. Yousefi and R.F. Saen, 2017. Forecasting efficiency of green suppliers by dynamic data envelopment analysis and artificial neural networks. J. Cleaner Prod., 142: 1098-1107.
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  30. Shabani, A., G.R. Faramarzi, R. Farzipoor Saen and M. Khodakarami, 2017. Simultaneous evaluation of efficiency, input effectiveness and output effectiveness: An application in after sales services agents. Benchmarking: Int. J., 24: 1854-1870.
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  31. Izadikhah, M., R.F. Saen and K. Ahmadi, 2017. How to assess sustainability of suppliers in volume discount context? A new data envelopment analysis approach. Transport. Res. Part D: Transport Environ., 51: 102-121.
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  32. Izadikhah, M., R. Farzipoor Saen and K. Ahmadi, 2017. How to assess sustainability of suppliers in the presence of dual-role factor and volume discounts? A data envelopment analysis approach. Asia-Pacific J. Operational Res., Vol. 34. 10.1142/S0217595917400164.
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  33. Goodarzi, M., P. Makvandi, R.F. Saen and M.D. Sagheb, 2017. What are causes of cash flow bullwhip effect in centralized and decentralized supply chains? Applied Math. Model., 44: 640-654.
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  34. Azadi, M., S.M. Mirhedayatian, R.F. Saen, M. Hatamzad and E. Momeni, 2017. Green supplier selection: A novel fuzzy double frontier data envelopment analysis model to deal with undesirable outputs and dual-role factors. Int. J. Ind. Syst. Eng., 25: 160-181.
  35. Azadi, M. and R. Farzipoor Saen, 2017. A new data envelopment analysis model for evaluating the performance of expert systems in supply chain management. Int. J. Operat. Res., 30: 65-82.
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  36. Yousefi, S., H. Shabanpour, R. Fisher and R.F. Saen, 2016. Evaluating and ranking sustainable suppliers by robust dynamic data envelopment analysis. Measurement, 83: 72-85.
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  37. Tavassoli, M., T. Badizadeh and R.F. Saen, 2016. Performance assessment of airlines using range-adjusted measure, strong complementary slackness condition and discriminant analysis. J. Air Transport Manage., 54: 42-46.
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  38. Shabani, A. and R.F. Saen, 2016. Developing imprecise dual-role hybrid measure of efficiency for international market selection using ternary variable. Int. J. Ind. Syst. Eng., 22: 305-331.
  39. Saen, R.F., R. Fisher and M. Mahdiloo, 2016. Sustainable supply chain modeling and optimization. Transport. Res. Part D, 48: 409-410.
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  40. Mahdiloo, M., A.H. Jafarzadeh, R.F. Saen, P. Tatham and R. Fisher, 2016. A multiple criteria approach to two-stage data envelopment analysis. Transport. Res. Part D: Transport Environ., 46: 317-327.
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  41. Khodakarami, M., A. Shabani and R.F. Saen, 2016. Concurrent estimation of efficiency, effectiveness and returns to scale. Int. J. Syst. Sci., 47: 1202-1220.
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  42. Jassbi, J., R.F. Saen, F.H. Lotfi and S.S. Hosseininia, 2016. A new hybrid decision making system for supplier selection. RAIRO-Operat. Res., 50: 645-664.
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  43. Izadikhah, M. and R.F. Saen, 2016. Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data. Transport. Res. Part D: Transport Environ., 49: 110-126.
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  44. Izadikhah, M. and R.F. Saen, 2016. A new preference voting method for sustainable location planning using geographic information system and data envelopment analysis. J. Cleaner Prod., 137: 1347-1367.
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  45. Azizi, H. and R. Farzipoor Saen, 2016. Selecting the best technology in presence of both cardinal and ordinal data: DEA with efficient and inefficient frontiers. J. Dev. Manage. Evolut., 26: 13-23.
  46. Yousefi, S., H. Shabanpour and R. Farzipoor Saen, 2015. Selecting the best supply chain by goal programming and network data envelopment analysis. RAIRO-Operat. Res., 49: 601-617.
  47. Toloo, M., R.F. Saen and M. Azadi, 2015. Obviating some of the theoretical barriers of data envelopment analysis-discriminant analysis: An application in predicting cluster membership of customers. J. Operat. Res. Soc., 66: 674-683.
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  48. Tavassoli, M., R. Farzipoor Saen and G.R. Faramarzi, 2015. Developing network DEA model for supply chain performance measurement in the presence of zero data. Expert Syst., 32: 381-391.
  49. Tavassoli, M., G.R. Faramarzi and R.F. Saen, 2015. A joint measurement of efficiency and effectiveness using network data envelopment analysis approach in the presence of shared input. Opsearch, 52: 490-504.
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  50. Tavassoli, M., G.R. Faramarzi and R. Farzipoor Saen, 2015. Ranking electricity distribution units using slacks-based measure, strong complementary slackness condition and discriminant analysis. Int. J. Elect. Power Energy Syst., 64: 1214-1220.
  51. Shabani, A., S.M.R. Torabipourv and R.F. Saen, 2015. A new super-efficiency dual-role FDH procedure: An application in dairy cold chain for vehicle selection. Int. J. Ship. Transport Logist., 7: 426-456.
  52. Shabani, A., S.M.R. Torabipour, R.F. Saen and M. Khodakarami, 2015. Distinctive data envelopment analysis model for evaluating global environment performance. Applied Math. Model., 39: 4385-4404.
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  53. Shabani, A. and R. Farzipoor Saen, 2015. Developing a novel data envelopment analysis model to determine prospective benchmarks of green supply chain in the presence of dual-role factor. Benchmark. Int. J., 22: 711-730.
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  54. Rashidi, K., A. Shabani and R.F. Saen, 2015. Using data envelopment analysis for estimating energy saving and undesirable output abatement: A case study in the Organization for Economic Co-Operation and Development (OECD) countries. J. Cleaner Prod., 105: 241-252.
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  55. Rashidi, K. and R.F. Saen, 2015. Measuring eco-efficiency based on green indicators and potentials in energy saving and undesirable output abatement. Energy Econ., 50: 18-26.
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  56. Momeni, E., M. Azadi and R. Farzipoor Saen, 2015. Measuring the efficiency of third party reverse logistics provider in supply chain by multi objective additive network DEA model. Int. J. Ship. Transport Logist., 7: 21-41.
  57. Mavi, R.K., R.F. Saen, N.K. Mavi, S.S. Taleshi and Z.R. Majd, 2015. Ranking bank branches using DEA and multivariate regression models. Int. J. Operat. Res., 24: 245-261.
  58. Mahdiloo, M., R.F. Saen and K.H. Lee, 2015. Technical, environmental and eco-efficiency measurement for supplier selection: An extension and application of data envelopment analysis. Int. J. Prod. Econ., 168: 279-289.
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  59. Khodakarami, M., A. Shabani, R.F. Saen and M. Azadi, 2015. Developing distinctive two-stage data envelopment analysis models: An application in evaluating the sustainability of supply chain management. Measurement, 70: 62-74.
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  60. Jafarzadeh, A., M. Mohammadkhani and R. Farzipoor Saen, 2015. Data Envelopment Analysis. Himeh Press, Tehran, Iran.
  61. Izadikhah, M. and R.F. Saen, 2015. A new data envelopment analysis method for ranking decision making units: an application in industrial parks. Expert Syst., 32: 596-608.
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  62. Faramarzi, G.R., M. Khodakarami, A. Shabani, R.F. Saen and F. Azad, 2015. New network data envelopment analysis approaches: An application in measuring sustainable operation of combined cycle power plants. J. Cleaner Prod., 108: 232-246.
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  63. Boudaghi, E. and R. Farzipoor Saen, 2015. Developing a model for determining optimal รง in DEA-discriminant analysis for predicting suppliers group membership in supply chain. OPSEARCH., 52: 134-155.
  64. Azizi, R., R.K. Matin and R.F. Saen, 2015. Ranking units and determining dominance relations in the cost efficiency analysis. RAIRO-Operat. Res., 49: 879-896.
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  65. Azizi, H., A.J. Shaerlar and R. Farzipoor Saen, 2015. A new approach for considering dual-role factor in supplier selection problem: DEA approach with efficient and inefficient frontiers. Prod. Operat. Manage., 2: 129-144.
  66. Azadi, M., M. Jafarian, S.M. Mirhedayatian and R.F. Saen, 2015. A novel fuzzy data envelopment analysis for measuring corporate sustainability performance. Int. J. Prod. Qual. Manage., 16: 312-324.
  67. Azadi, M., M. Jafarian, R. Farzipoor Saen and S.M. Mirhedayatian, 2015. A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Comput. Operat. Res., 54: 274-285.
  68. Ahmady, N., R.F. Saen, E. Ahmady and A.H. Sadeghi, 2015. Developing a fuzzy enhanced Russell measure for media selection. Int. J. Bus. Innovat. Res., 9: 470-485.
  69. Yousefi, S., H. Shabanpour, R. Farzipoor Saen and G.R. Faramarzi, 2014. Making an ideal decision-making unit using virtual network data envelopment analysis approach. Int. J. Bus. Perfor. Manage., 15: 316-328.
  70. Tavassoli, M., R. Farzipoor Saen and G.R. Faramarzi, 2014. A new super-efficiency model in the presence of both zero data and undesirable outputs. Sci. Iran., 21: 2360-2367.
  71. Tavassoli, M., H. Adldoost and R. Farzipoor Saen, 2014. Goal directed programming for determining process efficiency using data envelopment analysis. J. Math. Model. Algorith. Operat. Res., 13: 493-509.
  72. Tavassoli, M., G.R. Faramarzi and R. Farzipoor Saen, 2014. Multi-criteria ABC inventory classification using DEA-discriminant analysis to predict group membership of new items. Int. J. Applied Manage. Sci., 6: 171-189.
  73. Tavassoli, M., G.R. Faramarzi and R. Farzipoor Saen, 2014. Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input. J. Air Transport Manage., 34: 146-153.
  74. Tavassoli, M., G.R. Faramarzi and R. Farzipoor Saen, 2014. A joint measurement of efficiency and effectiveness for the best supplier selection using integrated data envelopment analysis approach. Int. J. Math. Operat. Res., 6: 70-83.
  75. Shabani, A., R. Farzipoor Saen and S.M.R. Torabipour, 2014. A new Data Envelopment Analysis (DEA) model to select eco-efficient technologies in the presence of undesirable outputs. Clean Technol. Environ. Policy, 16: 513-525.
  76. Shabani, A. and R. Farzipoor Saen, 2014. International market ranking using enhanced imprecise dual-role MAJ model. Int. J. Bus. Excellence, 7: 601-625.
  77. Noorizadeh, A., M. Mahdiloo, R. Farzipoor Saen, 2014. A new model for ranking suppliers in the presence of both undesirable and non-discretionary outputs. Int. J. Serv. Operat. Manage., 17: 280-293.
  78. Mirhedayatian, S.M., M. Azadi and R. Farzipoor Saen, 2014. A novel network data envelopment analysis model for evaluating green supply chain management. Int. J. Prod. Econ., 147: 544-554.
  79. Mahdiloo, M., M. Tavana, R. Farzipoor Saen and A. Noorizadeh, 2014. A game theoretic approach to modeling undesirable outputs and efficiency decomposition in data envelopment analysis. Applied Math. Comput., 244: 479-4929.
  80. Mahdiloo, M., A. Noorizadeh and R. Farzipoor Saen, 2014. Optimal direct mailing modeling based on data envelopment analysis. Expert Syst., 31: 101-109.
  81. Mahdiloo, M., A. Noorizadeh and R. Farzipoor Saen, 2014. Benchmarking suppliers performance when some factors play the role of both inputs and outputs: A new development to the slacks-based measure of efficiency. Benchmark. Int. J., 21: 792-813.
  82. Khodakarami, M., A. Shabani and R. Farzipoor Saen, 2014. A new look at measuring sustainability of industrial parks: A two-stage data envelopment analysis approach. Clean Technol. Environ. Policy, 16: 1577-1596.
  83. Faramarzi, G.R., M. Tavassoli and R. Farzipoor Saen, 2014. Network DEA: A new approach for determining component weight. Int. J. Manage. Sci. Eng. Manage., 9: 178-184.
  84. Eskandarinia, N., R. Farzipoor Saen and S.M. Shojaee, 2014. Strategic Management by Balanced Scorecard. Himeh Press, Tehran, Iran.
  85. Badizadeh, T. and R. Farzipoor Saen, 2014. Efficiency evaluation of production lines using maximal balanced index. Int. J. Manage. Decis. Making, 13: 302-317.
  86. Azadi, M., R. Farzipoor Saen and K. Hosseinzadeh Zoroufchi, 2014. A new goal directed benchmarking for supplier selection in the presence of undesirable outputs. Benchmark. Int. J., 21: 314-328.
  87. Azadi, M., A. Shabani, M. Khodakarami and R. Farzipoor Saen, 2014. Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers. Transport. Res. Part E: Logist. Transport. Rev., 70: 324-338.
  88. Azadi, M., A. Shabani and R. Farzipoor Saen, 2014. A new russell model for selecting suppliers. Int. J. Integr. Supply Manage., 9: 23-48.
  89. Azadi, M. and R. Farzipoor Saen, 2014. Developing a new theory of integer-valued data envelopment analysis for supplier selection in the presence of stochastic data. Int. J. Inform. Syst. Supply Chain Manage., 7: 80-103.
  90. Tavana, M., H. Mirzagoltabar, S.M. Mirhedayatian, R. Farzipoor Saen and M. Azadi, 2013. A new network epsilon-based dea model for supply chain performance evaluation. Comput. Ind. Eng., 66: 501-513.
  91. Shabani, A., R. Farzipoor Saen and H. Vazifehdoost, 2013. The use of data envelopment analysis for international market selection in the presence of multiple dual-role factors. Int. J. Bus. Inform. Syst., 13: 471-489.
  92. Noorizadeh, A., M. Mahdiloo and R. Farzipoor Saen, 2013. Using DEA cross-efficiency evaluation for suppliers ranking in the presence of non-discretionary inputs. Int. J. Shipp. Transport Logist., 5: 95-111.
  93. Noorizadeh, A., M. Mahdiloo and R. Farzipoor Saen, 2013. Evaluating relative value of customers via data envelopment analysis. J. Bus. Ind. Market., 28: 577-588.
  94. Nikoomaram, H., F.R. Roodposhti, R.F. Saen and B. Hemmati, 2013. The use of neural networks in forecasting type of CPAs opinions in auditing reports related to annual financial statements: A case study in Tehran stock exchange. Q. J. Quant. Res. Manage., 3: 47-70.
  95. Mirhedayatian, S.M., S.E. Vahdat, M.J. Jelodar and R.F. Saen, 2013. Welding process selection for repairing nodular cast iron engine block by integrated fuzzy data envelopment analysis and TOPSIS approaches. Mater. Des., 43: 272-282.
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  96. Mirhedayatian, M., M.J. Jelodar, S. Adnani, M. Akbarnejad and R.F. Saen, 2013. A new approach for prioritization in fuzzy AHP with an application for selecting the best tunnel ventilation system. Int. J. Adv. Manufact. Technol., 68: 2589-2599.
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  97. Mahdiloo, M., A. Noorizadeh and R.F. Saen, 2013. Direct mailing decisions based on the worst and best practice cross-efficiency evaluations. Int. J. Bus. Informat. Syst., 14: 182-201.
  98. Mahdiloo, M., A. Noorizadeh and R.F. Saen, 2013. A new model for suppliers ranking in the presence of both dual-role factors and undesirable outputs. Int. J. Logist. Syst. Manage., 15: 93-107.
  99. Farzipoor Saen, R., 2013. Using cluster analysis and DEA-discriminant analysis to predict group membership of new customers. Int. J. Bus. Excell., 6: 348-360.
  100. Farzipoor Saen, R. and S.M.R. Torabipour, 2013. Review of effective component's role on cold chain management performance by factor analysis approach for competitive organization. Iran. J. Trade Stud., 66: 73-94.
  101. Azadi, M., S.M. Mirhedayatian and R.F. Saen, 2013. A new fuzzy goal directed benchmarking for supplier selection. Int. J. Serv. Operat. Manage., 14: 321-335.
  102. Azadi, M. and R. Farzipoor Saen, 2013. Developing a chance-constrained free disposable hull model for selecting third-party reverse logistics providers. Int. J. Operat. Res. Inform. Syst., 4: 96-113.
  103. Azadi, M. and R. Farzipoor Saen, 2013. A combination of QFD and imprecise DEA with enhanced Russell graph measure: A case study in health care. Socio-Econ. Plan. Sci., 47: 281-291.
  104. Ahmady, N., M. Azadi, A.H. Sadeghi and R. Farzipoor Saen, 2013. A novel fuzzy data envelopment analysis model with double frontiers for supplier selection. Int. J. Logist. Res. Applic., 16: 87-98.
  105. Zoroufchi, K.H., M. Azadi and R.F. Saen, 2012. Developing A New Cross-Efficiency Model with Undesirable Outputs for Supplier Selection. Int. J. Ind. Syst. Eng., 12: 470-484.
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  106. Shabani, A., S.R. Farzipoor and S.M.R. Torabipour, 2012. A new benchmarking approach in cold chain. Applied Math. Modell., 36: 212-224.
    Direct Link  |  
  107. Saein, A.F. and R.F. Saen, 2012. Assessment of The Site Effect Vulnerability Within Urban Regions by Data Envelopment Analysis: A Case Study in Iran. Comput. Geosci., 48: 280-288.
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  108. Noorizadeh, A., M. Mahdiloo and S.R. Farzipoor, 2012. Suppliers Ranking in the Presence of Undesirable Outputs. Int. J. Logist. Syst. Manage., 11: 354-374.
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  109. Noorizadeh, A., M. Mahdiloo and R.F. Saen, 2012. Using DEA cross-efficiency evaluation for suppliers ranking in the presence of dual-role factors. Trends Appl. Sci. Res., 7: 314-323.
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  110. Noorizadeh, A., M. Mahdiloo and R.F. Saen, 2012. A New Approach for Considering A Dual-Role Factor in Data Envelopment Analysis. Int. J. Oper. Res., 14: 135-155.
    CrossRef  |  Direct Link  |  
  111. Noorizadeh, A., M. Mahdiloo and R. Farzipoor Saen, 2012. A data envelopment analysis model for selecting suppliers in the presence of both dual-role factors and non-discretionary inputs. Int. J. Inform. Decis. Sci., 4: 371-389.
  112. Momeni, E. and R.F. Saen, 2012. Developing a New Chance-Constrained Data Envelopment Analysis in the Presence of Stochastic Data. Int. J. Bus. Excellence, 5: 169-194.
    CrossRef  |  Direct Link  |  
  113. Mohammadkhani, M. and R. Farzipoor Saen, 2012. Design of Neural Networks. Himeh Press, Tehran, Iran.
  114. Mahdiloo, M., R.F. Saen and M. Tavana, 2012. A Novel Data Envelopment Analysis Model for Solving Supplier Selection Problems with Undesirable Outputs and Lack of Inputs. Int. J. Logist. Syst. Manage., 11: 285-305.
    CrossRef  |  Direct Link  |  
  115. Mahdiloo, M., A. Noorizadeh and R.F. Saen, 2012. Suppliers Ranking by Cross-Efficiency Evaluation in the Presence of Volume Discount Offers. Int. J. Serv. Oper. Manage., 11: 237-254.
    CrossRef  |  Direct Link  |  
  116. Lee, K.H. and S.R. Farzipoor, 2012. Measuring Corporate Sustainability Management: A Data Envelopment Analysis Approach. Int. J. Prod. Econ., 140: 219-226.
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  117. Farzipoor Saen, R., 2012. A New Look at Selecting Third-Party Reverse Logistics Providers. In: Information Technologies, Methods and Techniques of Supply Chain Management, Wang, J. (Ed.). IGI Global, Pennsylvania, USA., pp: 246-254.
  118. Farsijani, H., R. Farzipoor Saen and S.M.R. Torabipour, 2012. The role of entrepreneurship in cold chain management performance: A case study in meal industry. Entrepreneurship Dev., 4: 89-108, (In Persian).
  119. Azadi, M., R.F. Saen and M. Tavana, 2012. Supplier selection using chance-constrained data envelopment analysis with nondiscretionary factors and stochastic data. Int. J. Ind. Syst. Eng., 10: 167-196.
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  120. Azadi, M., K.H. Zoroufchi and R.F. Saen, 2012. A Combination of Russell Model and Neutral DEA for 3PL Provider Selection. Int. J. Productivity Qual. Manage., 10: 25-39.
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  121. Azadi, M. and R.F. Saen, 2012. Supplier Selection using a New Russell Model in the Presence of Undesirable Outputs and Stochastic Data. J. Appl. Sci., 12: 336-344.
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  122. Azadi, M. and R.F. Saen, 2012. Developing an Imprecise-WPF-SBM-Undesirable Model for Supplier Selection. Int. J. Bus. Innov. Res., 6: 597-614.
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  123. Azadi, M. and R.F. Saen, 2012. Developing a nondiscretionary slacks-based measure model for supplier selection in the presence of stochastic data. Res. J. Bus. Manage., 6: 103-120.
  124. Azadi, M. and R.F. Saen, 2012. Developing a new chance-constrained DEA model for suppliers selection in the presence of undesirable outputs. Int. J. Operat. Res., 13: 44-66.
    Direct Link  |  
  125. Azadi, M. and R.F. Saen, 2012. Developing a Worst Practice DEA Model for Selecting Suppliers in the Presence of Imprecise Data and Dual-Role Factor. Int. J. Appl. Decis. Sci., 5: 272-291.
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  126. Azadi, M. and R.F. Saen, 2012. Developing a Chance-Constrained Free Replicability Hull Model for Supplier Selection. Int. J. Logist. Syst. Manage., 12: 375-394.
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  127. Azadi, M. and R. Farzipoor Saen, 2012. Developing a neutral slacks-based measure for production line selection. Int. J. Operat. Res., 15: 359-370.
  128. Farzipoor Saen, R. and M. Gershon, 2012. Supplier Selection by the Pair of AR-NF-IDEA Models. In: Information Technologies, Methods and Techniques of Supply Chain Management, Wang, J. (Ed.). IGI Global, Pennsylvania, USA., pp: 349-367.
  129. Shabani, A., S.M.R. Torabipour and R.F. Saen, 2011. Container Selection in the Presence of Partial Dual-Role Factors. Int. J. Phys. Distrib. Logist. Manage., 41: 991-1008.
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  130. Saen, R.F., 2011. Media Selection in the Presence of Flexible Factors and Imprecise Data. J. Oper. Res. Soc., 62: 1695-1703.
    CrossRef  |  Direct Link  |  
  131. Saen, R.F., 2011. International Market Selection Using Advanced Data Envelopment Analysis. IMA J. Manage. Math., 22: 371-386.
    CrossRef  |  Direct Link  |  
  132. Saen, R.F. and M. Azadi, 2011. A Chance-Constrained Data Envelopment Analysis Approach for Strategy Selection. J. Model. Manage., 6: 200-214.
    CrossRef  |  Direct Link  |  
  133. Noorizadeh, A., M. Mahdiloo and S.R. Farzipoor, 2011. Supplier selection in the presence of dual-role factors, nondiscretionary inputs and weight restrictions. Int. J. Productivity Qual. Manage., 8: 134-152.
    CrossRef  |  Direct Link  |  
  134. Noorizadeh, A., M. Mahdiloo and S.R. Farzipoor, 2011. A new approach for considering a dual-role factor in data envelopment analysis. Int. J. Operat. Res. (In Press). .
  135. Noorizadeh, A., M. Mahdiloo and S.R. Farzipoor, 2011. A data envelopment analysis model for selecting suppliers in the presence of both dual-role factors and nondiscretionary inputs. Int. J. Inf. Decis. Sci. (In Press). .
  136. Noorizadeh, A., M. Mahdiloo and R.F. Saen, 2011. Incorporating undesirable outputs into the best and worst practice DEA models for customers scoring. Int. J. Modell. Oper. Manage., 1: 396-406.
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  137. Mirhedayatian, S.M., M. Jafarian and R.F. Saen, 2011. A multi-objective slack based measure of efficiency model for weight derivation in the analytic hierarchy process. J. Applied Sci., 11: 3338-3350.
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  138. Mirhedayatian, S.M. and R. Farzipoor Saen, 2011. A new approach for weight derivation using data envelopment analysis in the analytic hierarchy process. J. Operational Res. Soc., 62: 1585-1595.
    CrossRef  |  Direct Link  |  
  139. Mahdiloo, M., S.R. Farzipoor and M. Tavana, 2011. A novel data envelopment analysis model for solving supplier selection problems with undesirable outputs and lack of inputs. Int. J. Logist. Syst. Manage. (In Press). .
  140. Mahdiloo, M., A. Noorizadeh and S.R. Farzipoor, 2011. Suppliers ranking by cross-efficiency evaluation in the presence of volume discount offers. Int. J. Serv. Oper. Manage. (In Press). .
  141. Mahdiloo, M., A. Noorizadeh and S.R. Farzipoor, 2011. Developing a new data envelopment analysis model for customer value analysis. J. Ind. Manage. Optim., 7: 531-558.
    CrossRef  |  Direct Link  |  
  142. Mahdiloo, M., A. Noorizadeh and F.R. Saen, 2011. A new approach for considering a dual-role factor in supplier selection problem. Int. J. Acad. Res., 3: 261-266.
    Direct Link  |  
  143. Jassbi, J., R.F. Saen, F.H. Lotfi, S.S. Hosseininia and S. Khanmohammadi, 2011. A Hybrid Decision-Making System Using Data Envelopment Analysis and Fuzzy Models for Supplier Selection in The Presence of Multiple Decision Makers. Int. J. Ind. Math., 3: 193-212.
    Direct Link  |  
  144. Hosseinzadeh, Z.K., M. Azadi and S.R. Farzipoor, 2011. Developing a new cross-efficiency model with undesirable outputs for supplier selection. Int. J. Ind. Syst. Eng. (In Press). .
  145. Hemmasi, H., M. Talaeipour, H. Khademi-Eslam, S.R. Farzipoor and S.H. Pourmousa, 2011. Using DEA window analysis for performance evaluation of Iranian Wood Panels Industry. Afr. J. Agric. Res., 6: 1802-1806.
    CrossRef  |  Direct Link  |  
  146. Farzipoor, S.R., H. Farsijani and A. Shabani, 2011. Evaluating the best sales agents in cold chain by enhanced Russell graph efficiency measure model for benchmarking: A case study in an Iranian Dairy Co., Managerial Vision (In Press). .
  147. Farzipoor, S.R., 2011. A decision model for selecting third-party reverse logistics providers in the presence of both dual-role factors and imprecise data. Asia-Pacific J. Operational Res., 28: 239-254.
    Direct Link  |  
  148. Farzipoor, S.R., 2011. A decision model for selecting the best entry modes via data envelopment analysis. Int. J. Applied Decis. Sci., 4: 213-229.
    CrossRef  |  Direct Link  |  
  149. Farzipoor Saen, R., 2011. A New Optimization Method for Supplier Evaluation in the Context of Volume Discount. In: Supply Chain Optimization, Management and Integration: Emerging Applications, Wang, J. (Ed.). IGI Global, Pennsylvania, USA., pp: 64-75.
  150. Farsijani, H., S.R. Farzipoor and S.M.R. Torabipour, 2011. The role of information technology on performance of cold chain management in world class organizations (A research on food industries). J. Iran. Technol. Manage. (In Press). .
  151. Azadi, M., S.R. Farzipoor, 2011. A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors. Expert Syst. Appl., 38: 12231-12236.
    CrossRef  |  Direct Link  |  
  152. Azadi, M., S.R. Farzipoor and M. Tavana, 2011. Supplier selection using chance-constrained data envelopment analysis with nondiscretionary factors and stochastic data. Int. J. Ind. Syst. Eng. (In Press). .
  153. Azadi, M., R.F. Saen, 2011. Developing a WPF-CCR model for selecting suppliers in the presence of stochastic data. OR Insight, 24: 31-48.
    CrossRef  |  Direct Link  |  
  154. Azadi, M. and S.R. Farzipoor, 2011. Developing an output-oriented super SBM model with an application to third-party reverse logistics providers. J. Multi-Criteria Decis. Anal. (In Press). .
  155. Azadi, M. and S.R. Farzipoor, 2011. Developing a new chance-constrained DEA model for suppliers selection in the presence of undesirable outputs. Int. J. Operat. Res. (In Press). .
  156. Azadi, M. and S.R. Farzipoor, 2011. Developing a neutral slacks-based measure for production line selection. Int. J. Oper. Res. (In Press). .
  157. Azadi, M. and S.R. Farzipoor, 2011. Developing a Chance-Constrained Free Disposable Hull Model for Selecting Third-Party Reverse Logistics Providers. Int. J. Operat. Res. Inf. Sys. (In Press). .
  158. Azadi, M. and R.F. Saen, 2011. Developing an Output-Oriented Super Slacks-Based Measure Model with an Application to Third-Party Reverse Logistics Providers. J. Multi-Criteria Decis. Anal., 18: 267-277.
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  159. Zohrehbandian, M., F.R.Saen, 2010. A mathematical model for supplier selection in quantity discount environments. Int. J. Math. Operational Res., 2: 456-466.
    Direct Link  |  
  160. Saen, R.F., 2010. Restricting weights in supplier selection decisions in the presence of dual-role factors. Applied Math. Modell., 34: 2820-2830.
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  161. Saen, R.F., 2010. Media selection in the presence of flexible factors and imprecise data. J. Operat. Res. Soc., 10.1057/jors.2010.115.
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  162. Saen, R.F., 2010. Developing a new data envelopment analysis methodology for supplier selection in the presence of both undesirable outputs and imprecise data. Int. J. Adv. Manuf. Technol., 51: 1243-1250.
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  163. Saen, R.F., 2010. A new model for selecting third-party reverse logistics providers in the presence of multiple dual-role factors. Int. J. Adv. Manuf. Technol., 46: 405-410.
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  164. Saen, R.F., 2010. A decision model for selecting appropriate suppliers. Int. J. Adv. Oper. Manage., 2: 46-56.
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  165. Saen, F.R., 2010. The use of AR-IDEA approach for supplier selection problems. Aust. J. Basic Applied Sci., 4: 3053-3067.
    Direct Link  |  
  166. Saen, F.R., 2010. Technology selection in the presence of dual-role factors. Int. J. Adv. Oper. Manage., 2: 249-262.
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  167. Saen, F.R., 2010. Performance measurement of power plants in the existence of weight restrictions via slacks based model. Benchmarking: Int. J., 17: 677-691.
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  168. Saen, F.R., 2010. A new model for ranking 3pl providers. Aust. J. Basic Applied Sci., 4: 3762-3769.
    Direct Link  |  
  169. Saen, F.R., 2010. A new model for harmonizing scores growth among multiple criteria of excellence model of EFQM: A case study in sepahan industrial group Co. Int. J. Soc. Syst. Sci., 2: 100-108.
  170. Saen, F.R., 2010. A new look at selecting third-party reverse logistics providers. Int. J. Inf. Syst. Supply Chain Manag., 3: 58-67.
    CrossRef  |  
  171. Saen, F.R., 2010. A new algorithm for ranking suppliers in volume discount environments. Asia Pac. Manage. Rev., 15: 341-358.
    Direct Link  |  
  172. Saen, F.R. and M. Gershon, 2010. Supplier selection by the pair of AR-NF-IDEA models. Int. J. Inf. Syst. Supply Chain Manage., 3: 25-41.
    Direct Link  |  
  173. Sadeghi, S.A.H. and F.R. Saen, 2010. Developing an imprecise slack-based measure for supplier selection. Int. J. Decis. Sci., 1: 145-162.
    Direct Link  |  
  174. Saen, R.F., 2009. Using data envelopment analysis for ranking suppliers in the presence of nondiscretionary factors. Int. J. Procurement Manag., 2: 229-243.
    CrossRef  |  
  175. Saen, R.F., 2009. Supplier selection by the pair of nondiscretionaryors-imprecise data envelopment analysis models. J. Operational Res. Soc., 60: 1575-1582.
    CrossRef  |  
  176. Saen, R.F., 2009. A decision model for ranking suppliers in the presence of cardinal and ordinal data weight restrictions and nondiscretionary factors. Annals Operations Res., 172: 177-192.
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  177. Saen, F.R., 2009. The use of artificial neural networks for technology selection in the presence of both continuous and categorical data. World Applied Sci. J., 6: 1177-1189.
  178. Saen, F.R., 2009. Technology selection in the presence of imprecise data weight restrictions and nondiscretionary factors. Int. J. Adv. Manuf. Technol., 41: 827-838.
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  179. Saen, F.R., 2009. Suppliers selection in volume discount environments in the presence of both cardinal and ordinal data. Int. J. Inf. Syst. Supply Chain Manag., 2: 69-80.
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  180. Saen, F.R., 2009. A new approach for selecting slightly non-homogeneous vendors. J. Adv. Manag. Res., 6: 144-153.
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  181. Saen, F.R., 2009. A method for ranking efficient decision making units in the situation of nondiscretionary factors (Case Study: Islamic Azad University). J. Manag. Res., 19: 13-21.
  182. Saen, F.R., 2009. A mathematical programming approach for strategy ranking. Asia Pac. Manag. Review, 14: 109-120.
  183. Saen, F.R., 2009. A mathematical model for selecting third-party reverse logistics providers. Int. J. Procurement Manag., 2: 180-190.
    CrossRef  |  
  184. Saen, F.R. and M. Azadi, 2009. The use of super-efficiency analysis for strategy ranking. Int. J. Soc. Syst. Sci., 1: 281-292.
    CrossRef  |  Direct Link  |  
  185. Saen, R.F., 2008. Supplier selection by the new AR-IDEA model. Int. J. Adv. Manuf. Technol., 39: 1061-1070.
    CrossRef  |  
  186. Saen, F.R., 2008. A mathematical approach for technology selection in the presence of slightly nonhomogeneous technologies. Int. J. Applied Manag. Technol., 6: 107-121.
  187. Saen, F.R., 2008.. Using super-efficiency analysis for ranking suppliers in the presence of volume discount offers. Int. J. Phys. Distrib. Logis. Manage., 38: 637-651.
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  188. Saen, F.R. and M. Zohrehbandian, 2008. A data envelopment analysis approach for supplier selection in volume discount environments. Int. J. Procurement Manag., 1: 472-488.
    CrossRef  |  
  189. Saen, R.F., 2007. Suppliers selection in the presence of both cardinal and ordinal data. Eur. J. Operational Res., 183: 741-747.
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  190. Saen, F.R., 2007. A new mathematical approach for suppliers selection: Accounting for non-homogeneity is important. Applied Math. Comput., 185: 84-95.
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  191. Saen, F.R., 2006. Using Super-efficiency analysis for ranking technologies. WSEAS. Trans. Math., 5: 599-604.
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  192. Saen, F.R., 2006. Technologies ranking in the presence of both cardinal and ordinal data. Applied Math. Comput., 176: 476-487.
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  193. Saen, F.R., 2006. A decision model for selecting slightly non-homogeneous technologies. Applied Math. Comput., 177: 149-158.
    CrossRef  |  
  194. Saen, F.R., 2006.. A decision model for technology selection in the existence of both cardinal and ordinal data. Applied Math. Comput., 181: 1600-1608.
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  195. Saen, F.R., 2006. An algorithm for ranking technology suppliers in the presence of nondiscretionary factors. Applied Math. Comput., 181: 1616-1623.
    CrossRef  |  
  196. Saen, F.R., 2006. A decision model for selecting technology suppliers in the presence of nondiscretionary factors. Applied Math. Comput., 181: 1609-1615.
    CrossRef  |  
  197. Saen, R.F., 2005. Developing a nondiscretionary model of slacks-based measure in data envelopment analysis. Applied Math. Comput., 169: 1440-1447.
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  198. Saen, F.R., A. Memariani and H.F. Lotfi, 2005. The effect of correlation coefficient among multiple input vectors on the efficiency mean in data envelopment analysis. Applied Math. Comput., 162: 503-521.
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  199. Saen, F.R., A. Memariani and F.H. Lotfi, 2005. Determining relative efficiency of slighty non-homogeneous decision making units by data envelopment analysis: A case study in IROST. Applied Math. Comput., 165: 313-328.
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  200. Farzipoor, S.R., A. Memariani and L.F. Hosseinzadeh, 2003. The effect of correlation coefficient between input vectors on the efficiency mean in DEA. Sci. Res. J. Modarres Tech. Eng. .