GA-ANN model for optimizing the locations of tower crane and supply points for high-rise public housing construction

Abstract

Site layout planning is a complicated issue due to the existence of a vast number of trades and inter-related planning constraints. In this paper, artificial neural networks are used to model the non-linear operations of a key site facility: a tower crane — for high-rise public housing construction. Then genetic algorithms are used to determine the locations of the tower crane, supply points and demand points by optimizing the transportation time and costs. The scope of this study confines to a defined area of construction: the structural concrete-frame construction stage of public housing projects. The developed genetic algorithm model for site facility layout and the artificial neural network model for predicting tower-crane operations are evaluated using a practical example. The optimization results of the example are very promising and it demonstrates the application value of the models.