Graph-Based Automated Construction Scheduling without the Use of BIM

Abstract

The construction industry has been suffering from delay and cost overrun for decades. Experienced schedulers programs and allocate contingencies (both cost and time) based on professional experiences and gained knowledge. Such tacit knowledge has not been captured, stored, and shared with inexperienced schedulers. This paper proposes a Graph-based Automated Scheduling (GAS) method to capture, store and reuse the tacit knowledge in the construction schedules. The proposed GAS method takes construction schedules as input, extracts schedule features, classifies schedules into different types of sequences, selects and assembles sequences into schedules, and eventually optimises time-and cost-efficiency of assembled schedules. The GAS method is validated on two case studies. The results indicate that the automatically generated construction schedule is, on average, 6.70% closer to the actual schedule than the planned schedule . Different from existing automatic scheduling methods, GAS relies little on the availability and data richness of BIM models. Hence, GAS helps schedulers initiate new schedules more efficiently at the early construction stages

Building an Information Modeling-Based System for Automatically Generating the Assembly Sequence of Precast Concrete Components Using a Genetic Algorithm

“…Zhu et al (2023) [16] innovatively leveraged a game engine to create a reconfigurable assembly simulator by deploying Deep Reinforced Learning for automated assembly plans using robots on robot-based construction sites. Hong et al (2023) [22] employed a Graph-Based Automated Scheduling method, rearranging construction schedules by extracting activity characteristics to maximize efficiency in terms of cost and time. Moreover, Building Information Modeling (BIM) serves as a pivotal tool for extracting intercomponent relationships and determining optimal assembly schedules, as demonstrated by Liu et al (2014) [23].…”

Generation of Construction Scheduling through Machine Learning and BIM: A Blueprint

“…Several studies have used AI in coordination with 3D and 4D BIM to generate construction schedules [2,[13][14][15][16][17][18]. Kim et al [2] proposed a framework for automating schedule generation from BIM, where the sequencing rules are predefined.…”

“…Kim et al [2] proposed a framework for automating schedule generation from BIM, where the sequencing rules are predefined. Hong et al [14] proposed graph-based automated scheduling (GAS) to automatically store the best practices of past projects and reuse them to generate a new project schedule. Faghihi et al [15] proposed a method for retrieving information from BIM to develop construction sequencing using a genetic algorithm (GA).…”

Investigating the Use of ChatGPT for the Scheduling of Construction Projects

“…However, BIM models often do not include environmental factors, temporary structures, equipment and material availability, specific construction specifications, and the methodology of the building site. Therefore, the BIM-based automatic generation of schedules requires manual intervention to be practical [25,26].…”

“…Hong et al [26] proposed a graph-based construction scheduling approach. Their proposed approach stores past best practices and recycles the information to optimize the resource usage, task sequence, and duration of the new project.…”