Proactive Production Scheduling Approach for Off-Site Construction with Due Date Uncertainty

This study proposes a robust precast concrete (PC) production scheduling model for PC construction projects with schedule uncertainty by adopting a proactive scheduling approach. The proposed model consists of a PC production simulation module that simulates and evaluates the total tardiness of the schedule at a certain confidence level with contractor schedule uncertainty and a GA-based production schedule optimization module that finds an optimal schedule through iterative schedule generation and evaluation using a PC production simulation module. The experimental study shows that the proposed model can find the best schedule with 303.8 h of tardiness at a 100% confidence level, followed by NEHedd 324.7 h, basic GA 328.5 h, and EDD 335.8 h. The results of this study will help PC production schedulers to perform robustly despite contractors’ schedule changes and will thus contribute to the successful completion of PC construction projects.

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Publication Details

Journal
Applied Sciences
Published
2024-11-27
DOI
https://doi.org/10.3390/app142311017
Primary Topic
Scheduling and Optimization Algorithms
Type
article
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article

Proactive Production Scheduling Approach for Off-Site Construction with Due Date Uncertainty

Taehoon Kim, Yong‐Woo Kim
Applied Sciences
Scheduling and Optimization Algorithms
article

Proactive Production Scheduling Approach for Off-Site Construction with Due Date Uncertainty

Taehoon Kim, Yong‐Woo Kim
article en

Abstract

This study proposes a robust precast concrete (PC) production scheduling model for PC construction projects with schedule uncertainty by adopting a proactive scheduling approach. The proposed model consists of a PC production simulation module that simulates and evaluates the total tardiness of the schedule at a certain confidence level with contractor schedule uncertainty and a GA-based production schedule optimization module that finds an optimal schedule through iterative schedule generation and evaluation using a PC production simulation module. The experimental study shows that the proposed model can find the best schedule with 303.8 h of tardiness at a 100% confidence level, followed by NEHedd 324.7 h, basic GA 328.5 h, and EDD 335.8 h. The results of this study will help PC production schedulers to perform robustly despite contractors’ schedule changes and will thus contribute to the successful completion of PC construction projects.

Applied SciencesVol. 14(23)
Seoul National University of Science and Technology (KR), University of Washington (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 69%
Scheduling and Optimization Algorithms
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Proactive Production Scheduling Approach for Off-Site Construction with Due Date Uncertainty — Taehoon Kim, Yong‐Woo Kim · Applied Sciences (2024) | TGRS Research Map | TGRS