How to cite this paper
APA: Arjomandi, M & Mosallanezhad, B. (2022). Selecting maintenance strategy in a combined cycle power plant: An AHP model utilizing BOCR technique. Management Science Letters, 12(3), 153-164.
Chicago/Turabian: Arjomandi, M & Mosallanezhad, B. 2022. "Selecting maintenance strategy in a combined cycle power plant: An AHP model utilizing BOCR technique." Management Science Letters 12, no. 3 (2022): 153-164.
AMA: Arjomandi, M & Mosallanezhad, B. Selecting maintenance strategy in a combined cycle power plant: An AHP model utilizing BOCR technique. Management Science Letters. 2022;12(3):153-164.
References
Ahmadi, A., & Mosallanezhad, B. (2018). Using fuzzy FMEA to increase patient safety in fundamental pro-cesses of operating room. Journal of Industrial and Systems Engineering, 11(3), 146-166.
Alsyouf, I. (2004). Cost effective maintenance for competitive advantages (Doctoral dissertation, Växjö univer-sity press).
Arjomandi, M. A., Dinmohammadi, F., Mosallanezhad, B., & Shafiee, M. (2021). A fuzzy DEMATEL-ANP-VIKOR analytical model for maintenance strategy selection of safety critical assets. Advances in Mechani-cal Engineering, 13(4), 1687814021994965.
Asuquo, M. P., Wang, J., Zhang, L., & Phylip-Jones, G. (2019). Application of a multiple attribute group deci-sion making (MAGDM) model for selecting appropriate maintenance strategy for marine and offshore ma-chinery operations. Ocean Engineering, 179, 246-260.
Bashiri, M., Badri, H., & Hejazi, T. H. (2011). Selecting optimum maintenance strategy by fuzzy interactive linear assignment method. Applied Mathematical Modelling, 35(1), 152-164.
Bertolini, M., Bevilacqua, M., Ciarapica, F. E., & Giacchetta, G. (2009). Development of risk-based inspection and maintenance procedures for an oil refinery. Journal of loss prevention in the process industries, 22(2), 244-253.
Bevilacqua, M., & Braglia, M. (2000). The analytic hierarchy process applied to maintenance strategy selec-tion. Reliability Engineering & System Safety, 70(1), 71-83.
Borjalilu, N., & Ghambari, M. (2018). Optimal maintenance strategy selection based on a fuzzy analytical net-work process: A case study on a 5-MW powerhouse. International journal of engineering business man-agement, 10, 1847979018776172.
Bouzarour-Amokrane, Y., Tchangani, A., & Pérès, F. (2012). Defining and measuring risk and opportunity in BOCR framework for decision analysis. In 9e International Conference of Modeling and Simulation-MOSIM’12.
Bouzarour-Amokrane, Y., Tchangani, A., & Pérès, F. (2013). Evaluation process in end-of-life systems man-agement using BOCR analysis. IFAC Proceedings Volumes, 46(9), 105-110.
Erdoğmuş, Ş., Kapanoglu, M., & Koc, E. (2005). Evaluating high-tech alternatives by using analytic network process with BOCR and multiactors. Evaluation and Program Planning, 28(4), 391-399.
Feglar, T., Levy, J. K., Feglar, T., & Feglar, T. (2006). Advances in decision analysis and systems engineering for managing large-scale enterprises in a volatile world: Integrating benefits, opportunities, costs and risks (BOCR) with the business motivation model (BMM). Journal of Systems Science and Systems Engineer-ing, 15(2), 141-153.
Gedela, R. K., Mohan, K. K., & Prasad, V. K. (2018). Application of BOCR models in service oriented archi-tecture (SOA): study on model validation through quantification for QoS considerations. International Jour-nal of System Assurance Engineering and Management, 9(6), 1346-1354.
Lee, A. H. (2009). A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks. Expert systems with applications, 36(2), 2879-2893.
Liang, C., & Li, Q. (2008). Enterprise information system project selection with regard to BOCR. International journal of Project management, 26(8), 810-820.
Mohan, K. K., Reformat, M. Z., & Pedrycz, W. (2013, June). Interval-based analysis of BOCR (benefits, op-portunities, costs and risks) models evaluated by multiple experts. In 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS) (pp. 244-250). IEEE.
Mosallanezhad, B., Chouhan, V. K., Paydar, M. M., & Hajiaghaei-Keshteli, M. (2021b). Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic. Applied Soft Compu-ting, 112, 107809.
Mosallanezhad, B., Hajiaghaei-Keshteli, M., & Triki, C. (2021a). Shrimp closed-loop supply chain network de-sign. Soft Computing, 25(11), 7399-7422.
Nezami, F. G., & Yildirim, M. B. (2013). A sustainability approach for selecting maintenance strate-gy. International Journal of Sustainable Engineering, 6(4), 332-343.
Özcan, E., Yumuşak, R., & Eren, T. (2019). Risk based maintenance in the hydroelectric power plants. Energies, 12(8), 1502.
Saaty, T. L. (2004). Fundamentals of the analytic network process—multiple networks with benefits, costs, op-portunities and risks. journal of systems science and systems engineering, 13(3), 348-379.
Saaty, T. L., & Ozdemir, M. (2003). Negative priorities in the analytic hierarchy process. Mathematical and computer modelling, 37(9-10), 1063-1075.
Shafiee, M. (2015). Maintenance strategy selection problem: an MCDM overview. Journal of Quality in Maintenance Engineering.
Tabatabaee, S., Mahdiyar, A., Durdyev, S., Mohandes, S. R., & Ismail, S. (2019). An assessment model of benefits, opportunities, costs, and risks of green roof installation: A multi criteria decision making ap-proach. Journal of Cleaner Production, 238, 117956.
Tahmasdi, J., Ahmadi, A., & Mosallanezhad, B. (2021). Uncovering the hidden relation between air pollution and ischemic heart disease: Experience from Tehran. Journal of Industrial and Systems Engineering, 13(3), 216-242.
Wijnmalen, D. J. (2007). Analysis of benefits, opportunities, costs, and risks (BOCR) with the AHP–ANP: A critical validation. Mathematical and computer modelling, 46(7-8), 892-905.
Zaranezhad, A., Mahabadi, H. A., & Dehghani, M. R. (2019). Development of prediction models for repair and maintenance-related accidents at oil refineries using artificial neural network, fuzzy system, genetic algo-rithm, and ant colony optimization algorithm. Process Safety and Environmental Protection, 131, 331-348.
Zhao, B., Chen, H., Gao, D., & Xu, L. (2020). Risk assessment of refinery unit maintenance based on fuzzy second generation curvelet neural network. Alexandria Engineering Journal, 59(3), 1823-1831.
Alsyouf, I. (2004). Cost effective maintenance for competitive advantages (Doctoral dissertation, Växjö univer-sity press).
Arjomandi, M. A., Dinmohammadi, F., Mosallanezhad, B., & Shafiee, M. (2021). A fuzzy DEMATEL-ANP-VIKOR analytical model for maintenance strategy selection of safety critical assets. Advances in Mechani-cal Engineering, 13(4), 1687814021994965.
Asuquo, M. P., Wang, J., Zhang, L., & Phylip-Jones, G. (2019). Application of a multiple attribute group deci-sion making (MAGDM) model for selecting appropriate maintenance strategy for marine and offshore ma-chinery operations. Ocean Engineering, 179, 246-260.
Bashiri, M., Badri, H., & Hejazi, T. H. (2011). Selecting optimum maintenance strategy by fuzzy interactive linear assignment method. Applied Mathematical Modelling, 35(1), 152-164.
Bertolini, M., Bevilacqua, M., Ciarapica, F. E., & Giacchetta, G. (2009). Development of risk-based inspection and maintenance procedures for an oil refinery. Journal of loss prevention in the process industries, 22(2), 244-253.
Bevilacqua, M., & Braglia, M. (2000). The analytic hierarchy process applied to maintenance strategy selec-tion. Reliability Engineering & System Safety, 70(1), 71-83.
Borjalilu, N., & Ghambari, M. (2018). Optimal maintenance strategy selection based on a fuzzy analytical net-work process: A case study on a 5-MW powerhouse. International journal of engineering business man-agement, 10, 1847979018776172.
Bouzarour-Amokrane, Y., Tchangani, A., & Pérès, F. (2012). Defining and measuring risk and opportunity in BOCR framework for decision analysis. In 9e International Conference of Modeling and Simulation-MOSIM’12.
Bouzarour-Amokrane, Y., Tchangani, A., & Pérès, F. (2013). Evaluation process in end-of-life systems man-agement using BOCR analysis. IFAC Proceedings Volumes, 46(9), 105-110.
Erdoğmuş, Ş., Kapanoglu, M., & Koc, E. (2005). Evaluating high-tech alternatives by using analytic network process with BOCR and multiactors. Evaluation and Program Planning, 28(4), 391-399.
Feglar, T., Levy, J. K., Feglar, T., & Feglar, T. (2006). Advances in decision analysis and systems engineering for managing large-scale enterprises in a volatile world: Integrating benefits, opportunities, costs and risks (BOCR) with the business motivation model (BMM). Journal of Systems Science and Systems Engineer-ing, 15(2), 141-153.
Gedela, R. K., Mohan, K. K., & Prasad, V. K. (2018). Application of BOCR models in service oriented archi-tecture (SOA): study on model validation through quantification for QoS considerations. International Jour-nal of System Assurance Engineering and Management, 9(6), 1346-1354.
Lee, A. H. (2009). A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks. Expert systems with applications, 36(2), 2879-2893.
Liang, C., & Li, Q. (2008). Enterprise information system project selection with regard to BOCR. International journal of Project management, 26(8), 810-820.
Mohan, K. K., Reformat, M. Z., & Pedrycz, W. (2013, June). Interval-based analysis of BOCR (benefits, op-portunities, costs and risks) models evaluated by multiple experts. In 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS) (pp. 244-250). IEEE.
Mosallanezhad, B., Chouhan, V. K., Paydar, M. M., & Hajiaghaei-Keshteli, M. (2021b). Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic. Applied Soft Compu-ting, 112, 107809.
Mosallanezhad, B., Hajiaghaei-Keshteli, M., & Triki, C. (2021a). Shrimp closed-loop supply chain network de-sign. Soft Computing, 25(11), 7399-7422.
Nezami, F. G., & Yildirim, M. B. (2013). A sustainability approach for selecting maintenance strate-gy. International Journal of Sustainable Engineering, 6(4), 332-343.
Özcan, E., Yumuşak, R., & Eren, T. (2019). Risk based maintenance in the hydroelectric power plants. Energies, 12(8), 1502.
Saaty, T. L. (2004). Fundamentals of the analytic network process—multiple networks with benefits, costs, op-portunities and risks. journal of systems science and systems engineering, 13(3), 348-379.
Saaty, T. L., & Ozdemir, M. (2003). Negative priorities in the analytic hierarchy process. Mathematical and computer modelling, 37(9-10), 1063-1075.
Shafiee, M. (2015). Maintenance strategy selection problem: an MCDM overview. Journal of Quality in Maintenance Engineering.
Tabatabaee, S., Mahdiyar, A., Durdyev, S., Mohandes, S. R., & Ismail, S. (2019). An assessment model of benefits, opportunities, costs, and risks of green roof installation: A multi criteria decision making ap-proach. Journal of Cleaner Production, 238, 117956.
Tahmasdi, J., Ahmadi, A., & Mosallanezhad, B. (2021). Uncovering the hidden relation between air pollution and ischemic heart disease: Experience from Tehran. Journal of Industrial and Systems Engineering, 13(3), 216-242.
Wijnmalen, D. J. (2007). Analysis of benefits, opportunities, costs, and risks (BOCR) with the AHP–ANP: A critical validation. Mathematical and computer modelling, 46(7-8), 892-905.
Zaranezhad, A., Mahabadi, H. A., & Dehghani, M. R. (2019). Development of prediction models for repair and maintenance-related accidents at oil refineries using artificial neural network, fuzzy system, genetic algo-rithm, and ant colony optimization algorithm. Process Safety and Environmental Protection, 131, 331-348.
Zhao, B., Chen, H., Gao, D., & Xu, L. (2020). Risk assessment of refinery unit maintenance based on fuzzy second generation curvelet neural network. Alexandria Engineering Journal, 59(3), 1823-1831.