Currently, the main schedule-update processes are performed manually. These processes involve collecting as-built data from sites, analyzing the collected as-built data and comparing them with the planned progress, identifying the differences between the asbuilt progress and as-planned progress, and then modifying the schedule (Kiziltas and Akinci 2005; Liu and Shih 2009; Olawale and Sun 2013). Because the major processes are performed manually, considerable time is required to acquire and analyze data. In fact, project managers spend 30–50% of their working hours on collection and analysis of as-built data from sites (McCulloch 1997), requiring considerable efforts by project managers (Bell and McCullouch 1988; Fan et al. 2003). The reliability of the results of schedule updates depends on the subjective judgment of the persons who collect them (Liu et al. 1995). Consequently, the processes undertaken in schedule updates are not performed efficiently, objectively, and/or rapidly (Turkan et al. 2012).