Cost overrun estimation in the construction of high-rise buildings using fuzzy inference model

Abstract

Proper cost forecasting is a major parameter in the success of construction projects, and has a significant impact on various phases of a project, including its budget approval phase. Project managers usually look for solutions to reduce costs. It needs to identify the cost-rising factors, and to exclude them from projects. This study principally aimed at forecasting cost increase of high-rise building construction, using a neuro fuzzy inference model. In fact, the model is able to quantify cost overrun, resulted from each influencing factor, based on fuzzy logic. Through a vast literature review, 43 cost-influencing factors were identified, which then were reduced to 13, using the principal component analysis method, and experts’ opinions. The construction cost was then predicted by the inference model created, based on each factor. The results showed that the factor of “lack of commitment of the Ministry of Housing” had the greatest impact, while the factor of “not considering measures to resolve potential disputes” had the least impact on the estimation of cost overrun in high-rise buildings.