Proactive and Reactive Constraint Programming for Stochastic Project Scheduling with Maximal Time-Lags
Kim van den Houten, Léon Planken, Esteban Freydell, David M.J. Tax, Mathijs de Weerdt
Abstract
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 re-invoked 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
BibTeX
@article{Houten_Planken_Freydell_Tax_Weerdt_2025, title={Proactive and Reactive Constraint Programming for Stochastic Project Scheduling with Maximal Time-Lags}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/34854}, DOI={10.1609/aaai.v39i25.34854}, abstractNote={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 re-invoked 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}, number={25}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Houten, Kim van den and Planken, Léon and Freydell, Esteban and Tax, David M.J. and Weerdt, Mathijs de}, year={2025}, month={Apr.}, pages={26534-26541} }