Integration of Uncertain Real-Time Logistics Data for Reactive Scheduling Using Fuzzy Set Theory

This paper considers the integration of uncertain r eal-time logistics data for reactive construction scheduling. In order to manage a construction proje ct efficiently, an accurate schedule representing t he current project progress is inevitable. The quality and up-to-dateness of such a schedule depends on t he availability of real-time data. Typically, real-tim e logistics data contain information about the avai l bility of material, equipment and personnel as well as del ivery dates and site conditions. The accuracy and inherent uncertainty depends on the location where the real-time data was acquired. Currently, the integration of such data into a construction schedu le is a very time-consuming, manual and, thus, erro rprone process. Therefore, this paper proposes a met hodology that enables an automatic integration of s uch uncertain data into construction schedules. By inte grating uncertainties into the existing schedule th ir impacts on the construction work can be evaluated. For this, discrete event simulation is applied. In order to model uncertain input parameters for simulation models this methodology applies the fuzzy sets theo ry. In combination with alpha-cut sampling technique, d iscrete model input parameters are obtained. By applying reactive scheduling with several discrete ev nt simulation experiments, the results can be us ed to modify construction schedules according to agreed t imeframes and costs. In order to demonstrate and validate the presented approach an example is condu ted.