How to cite this paper
Zhang, Z., Guan, Z & Yue, L. (2023). Multi-fidelity simulation optimization for production releasing in re-entrant mixed-flow shops.International Journal of Industrial Engineering Computations , 14(1), 99-114.
Refrences
Albey, E., Bilge, Ü., & Uzsoy, R. (2014). An exploratory study of disaggregated clearing functions for production systems with multiple products. International Journal of Production Research, 52(18), 5301–5322.
Albey, E., & Bilge, U. (2011). A hierarchical approach to FMS planning and control with simulation-based capacity anticipation. International Journal of Production Research, 49(10-11), 3319-3342.
Asmundsson, J., Rardin, R. L., & Uzsoy, R. (2006). Tractable nonlinear production planning models for semiconductor wafer fabrication facilities. IEEE Transactions on Semiconductor Manufacturing, 19(1), 95–111.
Asmundsson, J., Rardin, R. L., Turkseven, C. H., & Uzsoy. (2009). Production planning with resources subject to congestion. Naval Research Logistics, 56(2), 142–157.
Baker, K. R. (1993). Requirements planning, in Handbooks in Operations Research and Management Science, 3, 571–627.
Bang, J., & Kim, Y. (2010). Hierarchical Production Planning for Semiconductor Wafer Fabrication Based on Linear Programming and Discrete-Event Simulation. IEEE Transactions on Automation Science and Engineering, 7(2), 326-336.
Billington, P., McClain, J., & Thomas, L. J. (1983). Mathematical programming approaches to capacity-constrained MRP systems: review, formulation, and problem reduction. Management Science, 29, 1126–1141.
Chang, P. C., Wang, Y. W., & Ting, C. J. (2008). A fuzzy neural network for the flow time estimation in a semiconductor manufacturing factory. International Journal of Production Research, 46(4), 1017–1029.
Chen, C., & Lee, L. (2010). Stochastic Simulation Optimization (An Optimal Computing Budget Allocation). Back Matter, 175-227.
Chen, R, Xu, J., Zhang, S., & Chen, C. (2015). An effective learning procedure for multi-fidelity simulation optimization with ordinal transformation. IEEE International Conference on Automation Science & Engineering. IEEE.
Chen, W., Wang, Z., & Chan, F. (2015). Robust Production Capacity Planning of a Wafer Fabrication System with Uncertain Wafer Lots Transfer Probabilities. IFAC PapersOnLine, 48(3), 1586-1591.
Chiu, C. C., & Lin, J. T. (2021). Hybrid Evolutionary Algorithm with an Optimal Sample Allocation Strategy for Multifidelity Simulation Optimization Problems. Asia-Pacific Journal of Operational Research, 38(02), 2050043.
Chiu, C., Zhang, S., Lin, J. T., Zhen, L., & Huang, E. (2016). Improving the efficiency of evolutionary algorithms for large-scale optimisation with multi-fidelity models. In 2016 Winter Simulation Conference, Washington, DC, USA, 815-826.
Chung, S. H., & Lai, C. (2006). Job releasing and throughput planning for wafer fabrication under demand fluctuating make-to-stock environment. The International Journal of Advanced Manufacturing Technology, 31(3), 316-327. doi: http://dx.doi.org/10.1007/s00170-005-0185-8
Fowler, J., & Mönch. L. (2017). Modeling and Analysis of Semiconductor Manufacturing. Advances in Modeling and Simulation.
Li, J., & Meerkov, S. (2009). Production Systems Engineering. Springer US.
Hackman, S. T., & R. C. Leachman. 1989. A general framework for modeling production. Management Science, 35(4), 478–495.
Hong, T., & Chien, C. (2020). A simulation-based dynamic scheduling and dispatching system with multi-criteria performance evaluation for Industry 3.5 and an empirical study for sustainable TFT-LCD array manufacturing. International Journal of Production Research, 58(24), 7531-7547.
Hsu, S. Y., & Sha, D. Y. (2004). Due date assignment using artificial neural networks under different shop floor control strategies. International Journal of Production Research, 42(9), 1727–1745.
Kacar, N. B., Irdem, D., & Uzsoy, R. (2012). An Experimental Comparison of Production Planning Using Clearing Functions and Iterative Linear Programming-Simulation Algorithms. IEEE Transactions on Semiconductor Manufacturing, 25(1), 104-117.
Kacar, N. B., Monch, L., & Uzsoy, R. (2013). Planning Wafer Starts using Nonlinear Clearing Functions: A Large-Scale Experiment. IEEE Transactions on Semiconductor Manufacturing, 26(4), 602-612.
Kacar, N. B., Monch, L., & Uzsoy, R. (2016). Modeling Cycle Times in Production Planning Models for Wafer Fabrication. IEEE Transactions on Semiconductor Manufacturing, 29(2), 153-167.
Kim, B., & Kim, S. (2001). Extended model for a hybrid production planning approach. International Journal of Production Economics, 73(1), 165-173.
Kim, S. H., & Lee, Y. H. (2016). Synchronized production planning and scheduling in semiconductor fabrication. Computers & Industrial Engineering, 96(6), 72-85.
Kopp, D., Monch, L., Pabst, D., & Stehli, M. (2019). Qualification Management in Wafer Fabs: Optimization Approach and Simulation-Based Performance Assessment. IEEE Transactions on Automation Science and Engineering, 17(1), 475-489.
Leachman, R. C. (1993). Modeling techniques for automated production planning in the semiconductor industry. in Optimization in Industry, T. A. Ciriani and R. C. Leachman, Eds. Chichester, U.K.: Wiley 1–30
Leachman, R. C. (2001). Semiconductor production planning. in Handbook of Applied Optimization, P. M. Pardalos and M. G. C. Resende, Eds. New York, NY, USA: Oxford Univ. Press 746–762.
Leachman, R. C., Benson, R., Liu, C., & Raar, D. J. (1996). IMPReSS: An automated production planning and delivery quotation system at Harris corporation—Semiconductor sector. Interfaces, 26(1), 6–37.
Leachman, R. C., & Raar, D. J. (1994). Optimized production planning and delivery quotation for the semiconductor industry. in Optimization in Industry 2, T. A. Ciriani and R. C. Leachman, Eds. Chichester, U.K.: Wiley 63–72.
Lee, L., Chen, C., Chew, E., Li, J., Nugroho, A., & Zhang, S. (2010). A Review of Optimal Computing Budget Allocation Algorithms for Simulation Optimization Problem. International Journal of Operations Research, 7(2), 19-31.
Lester, C., Yates, C., Giles, M., & Baker, R. (2014). An adaptive multi-level simulation algorithm for stochastic biological systems. Journal of Chemical Physics, 142(2), 024113.
Li, H., Li, Y., Lee, L., Chew, E., Pedrielli, G., & Chen, C. (2015). Multi-objective multi-fidelity optimisation with ordinal transformation and optimal sampling. In 2015 Winter Simulation Conference, California, USA, 3737-3748.
Lim, S., Kim, J., & Kim, H. (2014). Simultaneous order-lot pegging and wafer release planning for semiconductor wafer fabrication facilities. International Journal of Production Research, 52(11-12), 3710-3724.
Mather, H., & Plossl, G. W. (1978). Priority fixation versus throughput planning. Production and Inventory Management, 19, 27–51.
Milne, R. J., Mahapatra, S., & Wang, C. T. (2015). Optimizing planned lead times for enhancing performance of MRP systems. International Journal of Production Economics, 167(9), 220–231.
Missbauer, H. (2011). Order release planning with clearing functions: A queueing-theoretical analysis of the clearing function concept. International Journal of Production Economics, 131(1), 399-406.
Missbauer, H. (2020). Order release planning by iterative simulation and linear programming: theoretical foundation and analysis of its shortcomings. European Journal of Operational Research, 280(2), 495-507.
Orlicky, J. (1975). Material Requirements Planning: The New Way of Life in Production and Inventory Management. New York, NY, USA: McGraw-Hill.
Patil, R.J. (2008). Using ensemble and metaheuristics learning principles with artificial neural networks to improve due date prediction performance. International Journal of Production Research, 46(21), 6009–6027.
Pürgstaller, P., & Missbauer, H. (2011). Rule-based vs. optimisation-based order release in workload control: A simulation study of a MTO manufacturer. International Journal of Production Economics, 140(2).
Philipoom, P. R., Rees, L. P., & Wiegmann, L. (1994). Using Neural Networks to Determine Internally-Set Due-Date Assignments for Shop Scheduling. Decision Sciences, 25(5-6), 825–851.
Philipoom, P. R., Wiegmann, L., & Rees, L.P. (1997). Cost-based due-date assignment with the use of classical and neural-network approaches. Naval Research Logistics, 44(1), 21–46.
Qiu, Y., Song, J., & Liu, Z. (2016). A Simulation Optimisation on the Hierarchical Health Care Delivery System Patient Flow Based on Multi-Fidelity Models. International Journal of Production Research, 54(21-22), 1-16.
Singh, R., & Mathirajan, M. (2018). Experimental investigation for performance assessment of scheduling policies in semiconductor wafer fabrication—a simulation approach. The International Journal of Advanced Manufacturing Technology, 99(5), 1503-1520.
Schneckenreither, M., Haeussler, S., & Gerhold, C. (2021). Order release planning with predictive lead times: a machine learning approach. International Journal of Production Research, 59(11), 3285-3303.
Sébastien, P., & Mathieu, P. (2011). An interaction-oriented model for multi-scale simulation. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Catalonia, Spain, 332-337.
Selcuk, B., Fransoo, J. C., & De Kok, A. (2006). The effect of updating lead times on the performance of hierarchical planning systems. International Journal of Production Economics, 104(2), 427–440.
Shao, G., Jain, S., Laroque, C., Lee, L. H., Lendermann, P., & Rose, O. (2019). Digital Twin for Smart Manufacturing: The Simulation Aspect. In 2019 Winter Simulation Conference (WSC), National Harbor, MD, USA, 2085-2098.
Song, J., Qiu, Y., Xu, J., & Yang, F. (2019). Multi-fidelity sampling for efficient simulation-based decision making in manufacturing management. IISE Transactions, 51(7), 792-805.
Thuerer, M., Stevenson, M., Land, M., & Fredendall, L. (2019). On the combined effect of due date setting, order release, and output control: an assessment by simulation. International Journal of Production Research, 57(6), 1741-1755.
Vollmann, T. E., Berry, W. L., & Whybark, D. C. (1988). Manufacturing planning and control systems. Dow Jones-Irwin.
Whitt, W. (1983). The Queueing Network Analyser. Bell Labs Technical Journal, 62(9).
Wolosewicz, C., Dauzère-Pérès, S., & Aggoune, R. (2015). A lagrangian heuristic for an integrated lot-sizing and fixed scheduling problem. European Journal of Operational Research, 244(1), 3-12.
Xu J., Nelson, B., & Hong, L. (2010). Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation. Acm Transactions on Modeling & Computer Simulation, 20(1), 1-29.
Xu, J., Zhang, S., Huang, E., Chen, C., Lee, L., & Celik, N. (2014a). Efficient multi-fidelity simulation optimization. Proceedings of the Winter Simulation Conference, Savanah, GA.
Xu, J., Zhang, S., Huang, E., Chen, C., Lee, L., & Celik, N. (2014b). An Ordinal Transformation Framework for Multi-fidelity simulation-based optimisation. In 2014 IEEE International Conference on Automation Science and Engineering, Taiwan, China, 385-369.
Xu, J., Zhang, S., Huang, E., Chen, C., Lee, L., & Celik, N. (2016). MO2TOS: Multi-Fidelity Optimisation with Ordinal Transformation and Optimal Sampling. Asia-Pacific Journal of Operational Research, 33(3), 1650017.
Yanıkoğlu, I., Albey, E., & Uzsoy, R. (2017). Load Dependent Lead Time Modeling: A Robust Optimization Approach. Winter Simulation Conference.
Zhang, F., Song, J., Dai, Y., & Xu, J. (2020). Semiconductor wafer fabrication production planning using multi-fidelity simulation-based optimisation. International Journal of Production Research, 58(21), 6585-6600.
Zhang, Z., Guan, Z., Gong, Y., Luo, D., & Yue, L. (2022). Improved multi-fidelity simulation-based optimisation: application in a digital twin shop floor. International Journal of Production Research, 60(3), 1016-1035.
Ziarnetzky, T., Kacar, N., Monch, L., & Uzsoy, R. (2015). Simulation-based performance assessment of production planning formulations for semiconductor wafer fabrication. Winter Simulation Conference. IEEE.
Albey, E., & Bilge, U. (2011). A hierarchical approach to FMS planning and control with simulation-based capacity anticipation. International Journal of Production Research, 49(10-11), 3319-3342.
Asmundsson, J., Rardin, R. L., & Uzsoy, R. (2006). Tractable nonlinear production planning models for semiconductor wafer fabrication facilities. IEEE Transactions on Semiconductor Manufacturing, 19(1), 95–111.
Asmundsson, J., Rardin, R. L., Turkseven, C. H., & Uzsoy. (2009). Production planning with resources subject to congestion. Naval Research Logistics, 56(2), 142–157.
Baker, K. R. (1993). Requirements planning, in Handbooks in Operations Research and Management Science, 3, 571–627.
Bang, J., & Kim, Y. (2010). Hierarchical Production Planning for Semiconductor Wafer Fabrication Based on Linear Programming and Discrete-Event Simulation. IEEE Transactions on Automation Science and Engineering, 7(2), 326-336.
Billington, P., McClain, J., & Thomas, L. J. (1983). Mathematical programming approaches to capacity-constrained MRP systems: review, formulation, and problem reduction. Management Science, 29, 1126–1141.
Chang, P. C., Wang, Y. W., & Ting, C. J. (2008). A fuzzy neural network for the flow time estimation in a semiconductor manufacturing factory. International Journal of Production Research, 46(4), 1017–1029.
Chen, C., & Lee, L. (2010). Stochastic Simulation Optimization (An Optimal Computing Budget Allocation). Back Matter, 175-227.
Chen, R, Xu, J., Zhang, S., & Chen, C. (2015). An effective learning procedure for multi-fidelity simulation optimization with ordinal transformation. IEEE International Conference on Automation Science & Engineering. IEEE.
Chen, W., Wang, Z., & Chan, F. (2015). Robust Production Capacity Planning of a Wafer Fabrication System with Uncertain Wafer Lots Transfer Probabilities. IFAC PapersOnLine, 48(3), 1586-1591.
Chiu, C. C., & Lin, J. T. (2021). Hybrid Evolutionary Algorithm with an Optimal Sample Allocation Strategy for Multifidelity Simulation Optimization Problems. Asia-Pacific Journal of Operational Research, 38(02), 2050043.
Chiu, C., Zhang, S., Lin, J. T., Zhen, L., & Huang, E. (2016). Improving the efficiency of evolutionary algorithms for large-scale optimisation with multi-fidelity models. In 2016 Winter Simulation Conference, Washington, DC, USA, 815-826.
Chung, S. H., & Lai, C. (2006). Job releasing and throughput planning for wafer fabrication under demand fluctuating make-to-stock environment. The International Journal of Advanced Manufacturing Technology, 31(3), 316-327. doi: http://dx.doi.org/10.1007/s00170-005-0185-8
Fowler, J., & Mönch. L. (2017). Modeling and Analysis of Semiconductor Manufacturing. Advances in Modeling and Simulation.
Li, J., & Meerkov, S. (2009). Production Systems Engineering. Springer US.
Hackman, S. T., & R. C. Leachman. 1989. A general framework for modeling production. Management Science, 35(4), 478–495.
Hong, T., & Chien, C. (2020). A simulation-based dynamic scheduling and dispatching system with multi-criteria performance evaluation for Industry 3.5 and an empirical study for sustainable TFT-LCD array manufacturing. International Journal of Production Research, 58(24), 7531-7547.
Hsu, S. Y., & Sha, D. Y. (2004). Due date assignment using artificial neural networks under different shop floor control strategies. International Journal of Production Research, 42(9), 1727–1745.
Kacar, N. B., Irdem, D., & Uzsoy, R. (2012). An Experimental Comparison of Production Planning Using Clearing Functions and Iterative Linear Programming-Simulation Algorithms. IEEE Transactions on Semiconductor Manufacturing, 25(1), 104-117.
Kacar, N. B., Monch, L., & Uzsoy, R. (2013). Planning Wafer Starts using Nonlinear Clearing Functions: A Large-Scale Experiment. IEEE Transactions on Semiconductor Manufacturing, 26(4), 602-612.
Kacar, N. B., Monch, L., & Uzsoy, R. (2016). Modeling Cycle Times in Production Planning Models for Wafer Fabrication. IEEE Transactions on Semiconductor Manufacturing, 29(2), 153-167.
Kim, B., & Kim, S. (2001). Extended model for a hybrid production planning approach. International Journal of Production Economics, 73(1), 165-173.
Kim, S. H., & Lee, Y. H. (2016). Synchronized production planning and scheduling in semiconductor fabrication. Computers & Industrial Engineering, 96(6), 72-85.
Kopp, D., Monch, L., Pabst, D., & Stehli, M. (2019). Qualification Management in Wafer Fabs: Optimization Approach and Simulation-Based Performance Assessment. IEEE Transactions on Automation Science and Engineering, 17(1), 475-489.
Leachman, R. C. (1993). Modeling techniques for automated production planning in the semiconductor industry. in Optimization in Industry, T. A. Ciriani and R. C. Leachman, Eds. Chichester, U.K.: Wiley 1–30
Leachman, R. C. (2001). Semiconductor production planning. in Handbook of Applied Optimization, P. M. Pardalos and M. G. C. Resende, Eds. New York, NY, USA: Oxford Univ. Press 746–762.
Leachman, R. C., Benson, R., Liu, C., & Raar, D. J. (1996). IMPReSS: An automated production planning and delivery quotation system at Harris corporation—Semiconductor sector. Interfaces, 26(1), 6–37.
Leachman, R. C., & Raar, D. J. (1994). Optimized production planning and delivery quotation for the semiconductor industry. in Optimization in Industry 2, T. A. Ciriani and R. C. Leachman, Eds. Chichester, U.K.: Wiley 63–72.
Lee, L., Chen, C., Chew, E., Li, J., Nugroho, A., & Zhang, S. (2010). A Review of Optimal Computing Budget Allocation Algorithms for Simulation Optimization Problem. International Journal of Operations Research, 7(2), 19-31.
Lester, C., Yates, C., Giles, M., & Baker, R. (2014). An adaptive multi-level simulation algorithm for stochastic biological systems. Journal of Chemical Physics, 142(2), 024113.
Li, H., Li, Y., Lee, L., Chew, E., Pedrielli, G., & Chen, C. (2015). Multi-objective multi-fidelity optimisation with ordinal transformation and optimal sampling. In 2015 Winter Simulation Conference, California, USA, 3737-3748.
Lim, S., Kim, J., & Kim, H. (2014). Simultaneous order-lot pegging and wafer release planning for semiconductor wafer fabrication facilities. International Journal of Production Research, 52(11-12), 3710-3724.
Mather, H., & Plossl, G. W. (1978). Priority fixation versus throughput planning. Production and Inventory Management, 19, 27–51.
Milne, R. J., Mahapatra, S., & Wang, C. T. (2015). Optimizing planned lead times for enhancing performance of MRP systems. International Journal of Production Economics, 167(9), 220–231.
Missbauer, H. (2011). Order release planning with clearing functions: A queueing-theoretical analysis of the clearing function concept. International Journal of Production Economics, 131(1), 399-406.
Missbauer, H. (2020). Order release planning by iterative simulation and linear programming: theoretical foundation and analysis of its shortcomings. European Journal of Operational Research, 280(2), 495-507.
Orlicky, J. (1975). Material Requirements Planning: The New Way of Life in Production and Inventory Management. New York, NY, USA: McGraw-Hill.
Patil, R.J. (2008). Using ensemble and metaheuristics learning principles with artificial neural networks to improve due date prediction performance. International Journal of Production Research, 46(21), 6009–6027.
Pürgstaller, P., & Missbauer, H. (2011). Rule-based vs. optimisation-based order release in workload control: A simulation study of a MTO manufacturer. International Journal of Production Economics, 140(2).
Philipoom, P. R., Rees, L. P., & Wiegmann, L. (1994). Using Neural Networks to Determine Internally-Set Due-Date Assignments for Shop Scheduling. Decision Sciences, 25(5-6), 825–851.
Philipoom, P. R., Wiegmann, L., & Rees, L.P. (1997). Cost-based due-date assignment with the use of classical and neural-network approaches. Naval Research Logistics, 44(1), 21–46.
Qiu, Y., Song, J., & Liu, Z. (2016). A Simulation Optimisation on the Hierarchical Health Care Delivery System Patient Flow Based on Multi-Fidelity Models. International Journal of Production Research, 54(21-22), 1-16.
Singh, R., & Mathirajan, M. (2018). Experimental investigation for performance assessment of scheduling policies in semiconductor wafer fabrication—a simulation approach. The International Journal of Advanced Manufacturing Technology, 99(5), 1503-1520.
Schneckenreither, M., Haeussler, S., & Gerhold, C. (2021). Order release planning with predictive lead times: a machine learning approach. International Journal of Production Research, 59(11), 3285-3303.
Sébastien, P., & Mathieu, P. (2011). An interaction-oriented model for multi-scale simulation. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Catalonia, Spain, 332-337.
Selcuk, B., Fransoo, J. C., & De Kok, A. (2006). The effect of updating lead times on the performance of hierarchical planning systems. International Journal of Production Economics, 104(2), 427–440.
Shao, G., Jain, S., Laroque, C., Lee, L. H., Lendermann, P., & Rose, O. (2019). Digital Twin for Smart Manufacturing: The Simulation Aspect. In 2019 Winter Simulation Conference (WSC), National Harbor, MD, USA, 2085-2098.
Song, J., Qiu, Y., Xu, J., & Yang, F. (2019). Multi-fidelity sampling for efficient simulation-based decision making in manufacturing management. IISE Transactions, 51(7), 792-805.
Thuerer, M., Stevenson, M., Land, M., & Fredendall, L. (2019). On the combined effect of due date setting, order release, and output control: an assessment by simulation. International Journal of Production Research, 57(6), 1741-1755.
Vollmann, T. E., Berry, W. L., & Whybark, D. C. (1988). Manufacturing planning and control systems. Dow Jones-Irwin.
Whitt, W. (1983). The Queueing Network Analyser. Bell Labs Technical Journal, 62(9).
Wolosewicz, C., Dauzère-Pérès, S., & Aggoune, R. (2015). A lagrangian heuristic for an integrated lot-sizing and fixed scheduling problem. European Journal of Operational Research, 244(1), 3-12.
Xu J., Nelson, B., & Hong, L. (2010). Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation. Acm Transactions on Modeling & Computer Simulation, 20(1), 1-29.
Xu, J., Zhang, S., Huang, E., Chen, C., Lee, L., & Celik, N. (2014a). Efficient multi-fidelity simulation optimization. Proceedings of the Winter Simulation Conference, Savanah, GA.
Xu, J., Zhang, S., Huang, E., Chen, C., Lee, L., & Celik, N. (2014b). An Ordinal Transformation Framework for Multi-fidelity simulation-based optimisation. In 2014 IEEE International Conference on Automation Science and Engineering, Taiwan, China, 385-369.
Xu, J., Zhang, S., Huang, E., Chen, C., Lee, L., & Celik, N. (2016). MO2TOS: Multi-Fidelity Optimisation with Ordinal Transformation and Optimal Sampling. Asia-Pacific Journal of Operational Research, 33(3), 1650017.
Yanıkoğlu, I., Albey, E., & Uzsoy, R. (2017). Load Dependent Lead Time Modeling: A Robust Optimization Approach. Winter Simulation Conference.
Zhang, F., Song, J., Dai, Y., & Xu, J. (2020). Semiconductor wafer fabrication production planning using multi-fidelity simulation-based optimisation. International Journal of Production Research, 58(21), 6585-6600.
Zhang, Z., Guan, Z., Gong, Y., Luo, D., & Yue, L. (2022). Improved multi-fidelity simulation-based optimisation: application in a digital twin shop floor. International Journal of Production Research, 60(3), 1016-1035.
Ziarnetzky, T., Kacar, N., Monch, L., & Uzsoy, R. (2015). Simulation-based performance assessment of production planning formulations for semiconductor wafer fabrication. Winter Simulation Conference. IEEE.