On the project risk baseline: Integrating aleatory uncertainty into project scheduling

Obtaining a viable schedule baseline that meets all project constraints is one of the main issues for managers. The literature on this topic focuses mainly methods to obtain schedules meet resource restrictions and, more recently, financial limitations. provide different same project, and solutions with shortest duration are considered best-known project. However, no tools currently select which best performs in risk terms. To bridge gap, paper aims propose method selecting highest probability meeting deadline several alternative duration. do so, we integrating aleatory uncertainty into scheduling by quantifying execution alternatives proposed method, tested well-known repository benchmarking, can be applied any type help managers from duration, but lowest risk.