Automated Generation of Optimal Steel Sequences with Discrete Action, Status and Interaction Simulation in BIM
Construction Research Congress 2018
2018
- 6Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage6
- Abstract Views6
Conference Paper Description
4D BIM is one of the most advanced methods for construction planning. Using 4D BIMs properly illustrating hourly or finer details, various pre-construction analyses can become practical and potentially automated. One of the main challenges is intensive manual effort associated with creating detailed 4D BIMs. To minimize the manual efforts, past studies introduced computational methods that automatically generate construction schedules using 3D building models (BIMs). The state-of-the-art technologies, however, could generate only rough master-level plans inadequate for practical pre-construction analyses or optimization of the 4D BIMs. Therefore, this research presents a framework that automatically generates optimal 4D BIMs. Focusing on steel erection planning, the proposed method generates, analyzes, and optimizes steel erection sequences. A prototype software program was developed, which consists of two sub-systems, which are simulator and optimizer. The simulator numerically calculates actions, movements, status, and interactions involved in steel erection in a predefined interval. Then, the optimizer with a sequential combination of A star (A*) and genetic algorithm (GA) solves the computationally intensive optimization problem.
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