Hybrid Rescheduling Optimization Model under Disruptions in Precast Production Considering Real-World Environment
Publication: Journal of Construction Engineering and Management
Volume 147, Issue 4
Abstract
Increased emphasis is currently placed on precast production scheduling due to the upward-trending applications of precast technology. However, existing studies primarily focused on static scheduling, and few of them addressed dynamic rescheduling problems subject to disruptions from individual products without considering constraints in the practical environment. In this paper, a hybrid rescheduling optimization model for precast production is proposed to minimize rescheduling costs and ensure on-time delivery under disruptions of machine breakdown. The rescheduling was first optimized based on the genetic algorithm considering the idle time of multiple production lines, time intervals, and operation characteristics in precast production. Subsequently, the feasibility of potential reschedules was further verified via simulating production uncertainties in a real-world environment to achieve a trade-off between a high service level and profit maximization. Finally, a case study with different realistic scenarios was conducted to prove the superiority of the model in comparison with other methods. This methodology will increase the applicability of rescheduling methods in practice and reduce production costs of components in precast construction.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This research is supported by the National Natural Science Foundation of China (Grant No. 71901020) and China Postdoctoral Science Foundation (Grant No. 2019M650475).
References
Al-Bazi, A., and N. Dawood. 2010. “Developing crew allocation system for the precast industry using genetic algorithms.” Comput.-Aided Civ. Infrastruct. Eng. 25 (8): 581–595. https://doi.org/10.1111/j.1467-8667.2010.00666.x.
Aytug, H., M. A. Lawley, K. McKay, S. Mohan, and R. Uzsoy. 2005. “Executing production schedules in the face of uncertainties: A review and some future directions.” Eur. J. Oper. Res. 161 (1): 86–110. https://doi.org/10.1016/j.ejor.2003.08.027.
Campbell, H. G., R. A. Dudek, and M. L. Smith. 1970. “A heuristic algorithm for the job, machine sequencing problem.” Manage. Sci. 16 (10): B-630. https://doi.org/10.1287/mnsc.16.10.B630.
Chan, F. T. S., H. K. Chan, and H. C. W. Lau. 2002. “The state of the art in simulation study on FMS scheduling: A comprehensive survey.” Int. J. Adv. Manuf. Technol. 19 (11): 830–849. https://doi.org/10.1007/s001700200095.
Chan, W. T., and H. Hu. 2001. “An application of genetic algorithms to precast production scheduling.” Comput. Struct. 79 (17): 1605–1616. https://doi.org/10.1016/S0045-7949(01)00036-0.
Chan, W. T., and H. Hu. 2002. “Production scheduling for precast plants using a flow shop sequencing model.” J. Comput. Civ. Eng. 16 (3): 165–174. https://doi.org/10.1061/(ASCE)0887-3801(2002)16:3(165).
Chan, W. T., and T. H. Wee. 2003. “A multi-heuristic GA for schedule repair in precast plant production.” In Proc., 13th Int. Conf. on Automated Planning and Scheduling, 236–245. Menlo Park, CA: American Association for Artificial Intelligence Press.
Chen, J. H., L. R. Yang, and H. W. Tai. 2016. “Process reengineering and improvement for building precast production.” Autom. Constr. 68 (Aug): 249–258. https://doi.org/10.1016/j.autcon.2016.05.015.
Cheng, T., and R. Yan. 2009. “Integrating messy genetic algorithms and simulation to optimize resource utilization.” Comput-Aided Civ. Infrastruct. Eng. 24 (6): 401–415. https://doi.org/10.1111/j.1467-8667.2008.00588.x.
Dannenbring, D. G. 1977. “An evaluation of flow shop sequencing heuristics.” Manage. Sci. 23 (11): 1174–1182. https://doi.org/10.1287/mnsc.23.11.1174.
El-Abidi, K. M. A., and F. E. M. Ghazali. 2015. “Motivations and limitations of prefabricated building: An overview.” In Vol. 802 of Applied mechanics and materials, 668–675. Stafa-Zurich, Switzerland: Trans Tech.
Grefenstette, J. J. 1986. “Optimization of control parameters for genetic algorithms.” IEEE Trans. Syst. Man Cybern. 16 (1): 122–128. https://doi.org/10.1109/TSMC.1986.289288.
Gupta, J. N. D. 1971. “A functional heuristic algorithm for the flowshop scheduling problem.” J. Oper. Res. Soc. 22 (1): 39–47. https://doi.org/10.1057/jors.1971.18.
Hong, J., G. Q. Shen, C. Mao, Z. Li, and K. Li. 2016. “Life-cycle energy analysis of prefabricated building components: An input–output-based hybrid model.” J. Cleaner Prod. 112 (Part 4): 2198–2207. https://doi.org/10.1016/j.jclepro.2015.10.030.
Huo, Y., and H. Zhao. 2018. “Two machine scheduling subject to arbitrary machine availability constraint.” Omega 76 (Apr): 128–136. https://doi.org/10.1016/j.omega.2017.05.004.
Johnson, S. M. 1954. “Optimal two- and three-stage production schedules with setup times included.” Nav. Res. Logist. Q. 1 (1): 61–68. https://doi.org/10.1002/nav.3800010110.
Khalili, A., and D. K. H. Chua. 2013. “IFC-based framework to move beyond individual building elements toward configuring a higher level of prefabrication.” J. Comput. Civ. Eng. 27 (3): 243–253. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000203.
Ko, C. H. 2011. “Production control in precast fabrication: Considering demand variability in production schedules.” Can. J. Civ. Eng. 38 (2): 191–199. https://doi.org/10.1139/L10-123.
Ko, C. H., and S. F. Wang. 2010. “GA-based decision support systems for precast production planning.” Autom. Constr. 19 (7): 907–916. https://doi.org/10.1016/j.autcon.2010.06.004.
Ko, C. H., and S. F. Wang. 2011. “Precast production scheduling using multi-objective genetic algorithms.” Expert Syst. Appl. 38 (7): 8293–8302. https://doi.org/10.1016/j.eswa.2011.01.013.
Lee, J., and H. Hyun. 2019. “Multiple modular building construction project scheduling using genetic algorithms.” J. Constr. Eng. Manage. 145 (1): 04018116. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001585.
Leu, S. S., and S. T. Hwang. 2002. “GA-based resource-constrained flow-shop scheduling model for mixed precast production.” Autom. Constr. 11 (4): 439–452. https://doi.org/10.1016/S0926-5805(01)00083-8.
Li, H., Z. Li, L. X. Li, and B. Hu. 2000. “A production rescheduling expert simulation system.” Eur. J. Oper. Res. 124 (2): 283–293. https://doi.org/10.1016/S0377-2217(99)00381-1.
Li, S. H. A., H. P. Tserng, S. Y. L. Yin, and C. W. Hsu. 2010. “A production modeling with genetic algorithms for a stationary pre-cast supply chain.” Expert Syst. Appl. 37 (12): 8406–8416. https://doi.org/10.1016/j.eswa.2010.05.040.
Li, Z., and M. Ierapetritou. 2008. “Process scheduling under uncertainty: Review and challenges.” Comput. Chem. Eng. 32 (4–5): 715–727. https://doi.org/10.1016/j.compchemeng.2007.03.001.
Ouelhadj, D., and S. Petrovic. 2009. “A survey of dynamic scheduling in manufacturing systems.” J. Scheduling 12 (4): 417. https://doi.org/10.1007/s10951-008-0090-8.
Palmer, D. S. 1965. “Sequencing jobs through a multi-stage process in the minimum total time—A quick method of obtaining a near optimum.” J. Oper. Res. Soc. 16 (1): 101–107. https://doi.org/10.1057/jors.1965.8.
Persson, F., and M. Araldi. 2009. “The development of a dynamic supply chain analysis tool—Integration of SCOR and discrete event simulation.” Int. J. Prod. Econ. 121 (2): 574–583. https://doi.org/10.1016/j.ijpe.2006.12.064.
Schaffer, J. D., R. A. Caruana, J. L. Eshelman, and R. Das. 1989. “A study of control parameters affecting online performance of genetic algorithms for function optimization.” In Proc., 3rd IEEE Int. Conf., Genetic Algorithms, 51–60. New York: Morgan Kaufmann Publishers.
Suresh, V., and D. Chaudhuri. 1993. “Dynamic scheduling—A survey of research.” Int. J. Prod. Econ. 32 (1): 53–63. https://doi.org/10.1016/0925-5273(93)90007-8.
Vieira, G. E., J. W. Herrmann, and E. Lin. 2003. “Rescheduling manufacturing systems: A framework of strategies, policies, and methods.” J. Scheduling 6 (1): 39–62. https://doi.org/10.1109/TSMC.1986.289288.
Wang, Z., and H. Hu. 2017. “Improved precast production—Scheduling model considering the whole supply chain.” J. Comput. Civ. Eng. 31 (4): 04017013. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000667.
Wang, Z., and H. Hu. 2018. “Dynamic response to demand variability for precast production rescheduling with multiple lines.” Int. J. Prod. Res. 56 (16): 5386–5401. https://doi.org/10.1080/00207543.2017.1414970.
Wang, Z., H. Hu, and J. Gong. 2018a. “Framework for modeling operational uncertainty to optimize offsite production scheduling of precast components.” Autom. Constr. 86: 69–80. https://doi.org/10.1109/TSMC.1986.289288.
Wang, Z., H. Hu, and J. Gong. 2018b. “Modeling worker competence to advance precast production scheduling optimization.” J. Constr. Eng. Manage. 144 (11): 04018098. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001556.
Wang, Z., H. Hu, and J. Gong. 2018c. “Simulation based multiple disturbances evaluation in the precast supply chain for improved disturbance prevention.” J. Cleaner Prod. 177: 232–244. https://doi.org/10.1109/TSMC.1986.289288.
Wang, Z., H. Hu, and W. Zhou. 2017. “RFID enabled knowledge-based precast construction supply chain.” Comput.-Aided Civ. Infrastruct. Eng. 32 (6): 499–514. https://doi.org/10.1111/mice.12254.
Wang, Z., T. Wang, H. Hu, J. Gong, X. Ren, and Q. Xiao. 2020. “Blockchain-based framework for improving supply chain traceability and information sharing in precast construction.” Autom. Constr. 111 (Mar): 103063. https://doi.org/10.1016/j.autcon.2019.103063.
Warszawski, A. 1984. “Production planning in prefabrication plant.” Build. Environ. 19 (2): 139–147. https://doi.org/10.1016/0360-1323(84)90039-8.
Yang, Z., Z. Ma, and S. Wu. 2016. “Optimized flowshop scheduling of multiple production lines for precast production.” Autom. Constr. 72 (Part 3): 321–329. https://doi.org/10.1016/j.autcon.2016.08.021.
Yuan, J., and Y. Mu. 2007. “Rescheduling with release dates to minimize makespan under a limit on the maximum sequence disruption.” Eur. J. Oper. Res. 182 (2): 936–944. https://doi.org/10.1016/j.ejor.2006.07.026.
Zhai X., R. L. K. Tiong, H. C. Bjornsson, and D. K. Chua. 2006. “A simulation-GA based model for production planning in precast plant.” In Proc., 2006 Winter Simulation Conf., 1796–1803. New York: IEEE.
Zhai, Y., R. Y. Zhong, Z. Li, and G. Huang. 2017. “Production lead-time hedging and coordination in prefabricated construction supply chain management.” Int. J. Prod. Res. 55 (14): 3984–4002. https://doi.org/10.1080/00207543.2016.1231432.
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Received: May 2, 2020
Accepted: Aug 28, 2020
Published online: Jan 31, 2021
Published in print: Apr 1, 2021
Discussion open until: Jun 30, 2021
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