Buffer sizing of critical chain based on attribute optimization

Abstract

This research proposes an innovative buffer sizing method based on optimizing attributes in order to improve the efficiency of buffer management and optimize the estimation accuracy of a project buffer. The Monte Carlo simulation results show that the buffer obtained using this method is smaller than the cut and paste method, but larger than the root square error method. These findings indicate that the proposed method gives full consideration to the interdependencies between the activities, thus avoiding the excessive protection provided by the cut and paste method and overcoming the insufficient consideration of root square error method project attributes based on the central limit theorem. The proposed method can provide the project with effective protection, along with an appropriate buffer size.