Generating Robust Schedules Subject to Resource and Duration Uncertainties

We consider the Resource-Constrained Project Scheduling Problem with minimal and maximal time lags under resource and duration uncertainties. To manage resource uncertainties, we build upon the work of Lambrechts et al 2007 and develop a method to analyze the effect of resource breakdowns on activity durations. We then extend the robust local search framework of Lau et al 2007 with additional considerations on the impact of unexpected resource breakdowns to the project makespan, so that partial order schedules (POS) can absorb both resource and duration uncertainties. Experiments show that our proposed model is capable of addressing the uncertainty of resources, where the most robust POS is generated to minimize the robust makespan with statistical guarantee. Compared with prevailing methods, our method is also capable of achieving more feasible solutions with better robust makespan.

• Type: Conference
• Year: 2008
• Where: AIPS
• Authors: Na Fu, Hoong Chuin Lau, Fei Xiao
• Keywords: AIPS 2008, Artificial Intelligence, Duration Uncertainties, Resource Breakdowns, Robust