Genetic algorithm-based steel erection planning model for a construction automation system

Over the past decade, construction project managers have been forced increasingly to cope with the lack of a skilled workforce and increases in hazardous circumstances for human operations. Construction automation systems have been widely proposed as alternatives to overcome these difficulties and to raise construction quality, enhance productivity, and improve safety. To demonstrate the efficiency of a construction automation system, we introduce a Genetic Algorithm-based Repetitive Tasks Simulation (GARTS) model for planning steel erection in high-rise building construction. This model produces an optimized movement path of a bolting robot for fabricating steel structures, proposes a collaboration plan between a robot and a worker, and quantifies the uncertainty of the duration of steel erection. As an illustrative case, the so-called robot-based construction automation system (RCA) was applied to a pilot project. The results showed the model's capacities and justified its application to other extended types of robotic construction systems.

► We introduce a genetic algorithm-based repetitive tasks simulation model.
► The model produces an optimized movement path of a bolting robot.
► The model proposes a collaboration plan between a robot and a worker.
► The model is used for planning steel erection in high-rise building construction.