Proactive and Reactive Constraint Programming for Stochastic Project Scheduling with Maximal Time-Lags
This addresses scheduling challenges in project management, but it is incremental as it builds on existing constraint programming and temporal network methods.
The study tackled the stochastic resource-constrained project scheduling problem with maximal time lags by comparing proactive and reactive scheduling methods, finding that an STNU-based algorithm performed best in solution quality with good computation times.
This study investigates scheduling strategies for the stochastic resource-constrained project scheduling problem with maximal time lags (SRCPSP/max)). Recent advances in Constraint Programming (CP) and Temporal Networks have reinvoked interest in evaluating the advantages and drawbacks of various proactive and reactive scheduling methods. First, we present a new, CP-based fully proactive method. Second, we show how a reactive approach can be constructed using an online rescheduling procedure. A third contribution is based on partial order schedules and uses Simple Temporal Networks with Uncertainty (STNUs). Our statistical analysis shows that the STNU-based algorithm performs best in terms of solution quality, while also showing good relative offline and online computation time.