Computational modeling study demonstrates a 15.47% reduction in scheduling time for railway hub foundation pit construction, indicating improved operational efficiency in complex building projects.
The construction of large-scale buildings often faces extended production cycles due to inefficiencies in scheduling processes. To address this challenge, a timed Petri net model was developed to analyze and optimize construction scheduling. Based on the Petri net transition sequence, a scheduling optimization model was proposed. To solve the model efficiently, an improved brainstorming optimization (BSO) algorithm was introduced. Compared with the classical BSO, two targeted enhancements were introduced: a problem-specific encoding and decoding method for Petri net transition sequences to ensure solution feasibility and an embedded simulated annealing local search mechanism to prevent premature convergence in later iterations. The proposed methodology was validated using real-world data from a large high-speed railway hub foundation pit construction project. Results demonstrated a significant reduction of 531 working hours in the total scheduling time, representing a 15.47% improvement in scheduling efficiency compared to traditional sequential scheduling methods. This approach not only shortened the scheduling cycle and enhanced production efficiency but also offered an innovative solution to address scheduling issues in complex construction processes.
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Wang et al. (2026) studied this question.
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