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Science Alert
 
    Publisher: Asian Network for Scientific Information
   
  Journal of Applied Sciences seeks to promote and disseminate the knowledge by publishing original research findings, review articles and short communications in the broad field of applied sciences. Scope of the journal includes: Biology, chemistry, physics, environmental, business and economics, finance, mathematics and statistics, geology, engineering, computer science, social sciences, natural and technological sciences, linguistics, medicine and architecture, food science, environmental science, agricultural engineering. Journal of Applied Sciences now accepting new submissions. Submit your best paper via online submission system.
  Editor-in-Chief:  Gazi Mahabubul Alam
 
 
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.
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.
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.
Azadi, M. and R. Farzipoor Saen, 2012. Developing a neutral slacks-based measure for production line selection. Int. J. Operat. Res., 15: 359-370.
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.
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.
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.
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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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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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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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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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.
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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.
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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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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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). .
Azadi, M. and S.R. Farzipoor, 2011. Developing a neutral slacks-based measure for production line selection. Int. J. Oper. Res. (In Press). .
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). .
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). .
Azadi, M., A. Shabani and R. Farzipoor Saen, 2014. A new russell model for selecting suppliers. Int. J. Integr. Supply Manage., 9: 23-48.
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.
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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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.
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.
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.
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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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.
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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.
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.
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). .
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.
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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.
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).
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.
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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Badizadeh, T. and R. Farzipoor Saen, 2014. Efficiency evaluation of production lines using maximal balanced index. Int. J. Manage. Decis. Making, 13: 302-317.
Boudaghi, E. and R. Farzipoor Saen, 2015. Developing a model for determining optimal ç in DEA-discriminant analysis for predicting suppliers group membership in supply chain. OPSEARCH., 52: 134-155.
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.
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Eskandarinia, N., R. Farzipoor Saen and S.M. Shojaee, 2014. Strategic Management by Balanced Scorecard. Himeh Press, Tehran, Iran.
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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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.
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).
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). .
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.
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.
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.
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.
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.
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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.
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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. .
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). .
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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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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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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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.
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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). .
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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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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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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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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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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Jafarzadeh, A., M. Mohammadkhani and R. Farzipoor Saen, 2015. Data Envelopment Analysis. Himeh Press, Tehran, Iran.
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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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.
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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.
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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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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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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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.
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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.
Mahdiloo, M., A. Noorizadeh and R. Farzipoor Saen, 2014. Optimal direct mailing modeling based on data envelopment analysis. Expert Syst., 31: 101-109.
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.
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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.
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.
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.
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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). .
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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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.
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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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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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.
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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). .
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.
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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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.
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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.
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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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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Mohammadkhani, M. and R. Farzipoor Saen, 2012. Design of Neural Networks. Himeh Press, Tehran, Iran.
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.
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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.
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.
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.
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.
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.
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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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.
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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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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). .
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). .
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.
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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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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.
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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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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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.
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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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Saen, F.R. and M. Azadi, 2009. The use of super-efficiency analysis for strategy ranking. Int. J. Soc. Syst. Sci., 1: 281-292.
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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.
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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.
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Saen, F.R., 2006. A decision model for selecting technology suppliers in the presence of nondiscretionary factors. Applied Math. Comput., 181: 1609-1615.
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Saen, F.R., 2006. An algorithm for ranking technology suppliers in the presence of nondiscretionary factors. Applied Math. Comput., 181: 1616-1623.
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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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Saen, F.R., 2006. A decision model for selecting slightly non-homogeneous technologies. Applied Math. Comput., 177: 149-158.
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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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Saen, F.R., 2006. Using Super-efficiency analysis for ranking technologies. WSEAS. Trans. Math., 5: 599-604.
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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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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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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.
Saen, F.R., 2009. A mathematical model for selecting third-party reverse logistics providers. Int. J. Procurement Manag., 2: 180-190.
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Saen, F.R., 2009. A mathematical programming approach for strategy ranking. Asia Pac. Manag. Review, 14: 109-120.
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.
Saen, F.R., 2009. A new approach for selecting slightly non-homogeneous vendors. J. Adv. Manag. Res., 6: 144-153.
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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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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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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.
Saen, F.R., 2010. A new algorithm for ranking suppliers in volume discount environments. Asia Pac. Manage. Rev., 15: 341-358.
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Saen, F.R., 2010. A new look at selecting third-party reverse logistics providers. Int. J. Inf. Syst. Supply Chain Manag., 3: 58-67.
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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.
Saen, F.R., 2010. A new model for ranking 3pl providers. Aust. J. Basic Applied Sci., 4: 3762-3769.
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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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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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Saen, F.R., 2010. The use of AR-IDEA approach for supplier selection problems. Aust. J. Basic Applied Sci., 4: 3053-3067.
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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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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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Saen, R.F. and M. Azadi, 2011. A Chance-Constrained Data Envelopment Analysis Approach for Strategy Selection. J. Model. Manage., 6: 200-214.
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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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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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Saen, R.F., 2008. Supplier selection by the new AR-IDEA model. Int. J. Adv. Manuf. Technol., 39: 1061-1070.
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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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Saen, R.F., 2009. Supplier selection by the pair of nondiscretionaryors-imprecise data envelopment analysis models. J. Operational Res. Soc., 60: 1575-1582.
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Saen, R.F., 2009. Using data envelopment analysis for ranking suppliers in the presence of nondiscretionary factors. Int. J. Procurement Manag., 2: 229-243.
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Saen, R.F., 2010. A decision model for selecting appropriate suppliers. Int. J. Adv. Oper. Manage., 2: 46-56.
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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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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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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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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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Saen, R.F., 2011. International Market Selection Using Advanced Data Envelopment Analysis. IMA J. Manage. Math., 22: 371-386.
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Saen, R.F., 2011. Media Selection in the Presence of Flexible Factors and Imprecise Data. J. Oper. Res. Soc., 62: 1695-1703.
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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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Shabani, A. and R. Farzipoor Saen, 2014. International market ranking using enhanced imprecise dual-role MAJ model. Int. J. Bus. Excellence, 7: 601-625.
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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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.
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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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.
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.
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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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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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.
Shabani, A., S.R. Farzipoor and S.M.R. Torabipour, 2012. A new benchmarking approach in cold chain. Applied Math. Modell., 36: 212-224.
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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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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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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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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.
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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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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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.
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.
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.
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.
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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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.
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.
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.
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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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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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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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.
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.
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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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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Zohrehbandian, M., F.R.Saen, 2010. A mathematical model for supplier selection in quantity discount environments. Int. J. Math. Operational Res., 2: 456-466.
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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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