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).
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 147 • Issue 4 • April 2021
Copyright
© 2021 American Society of Civil Engineers.
History
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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