The Resource-Constrained Project Scheduling Problem (RCPSP) is a well-known scheduling problem aimed at minimizing the makespan of a project subject to temporal and resource constraints. In this paper we show that hard RCPSPs can be efficiently tackled by a portfolio approach that combines the strengths of different constraint solvers Our approach seeks to predict and run in parallel the best solvers for a new, unseen RCPSP instance by enabling the bound communication between them. This on-average allows to outperform the oracle solver that always chooses the best available solver for any given instance.
Parallelizing constraint solvers for hard RCPSP instances / Amadini, Roberto; Gabbrielli, Maurizio; Mauro, Jacopo. - STAMPA. - 10079:(2016), pp. 227-233. (Intervento presentato al convegno 10th International Conference on Learning and Intelligent Optimization, LION 10 tenutosi a ita nel 2016) [10.1007/978-3-319-50349-3_16].
Parallelizing constraint solvers for hard RCPSP instances
GABBRIELLI, MAURIZIO;
2016
Abstract
The Resource-Constrained Project Scheduling Problem (RCPSP) is a well-known scheduling problem aimed at minimizing the makespan of a project subject to temporal and resource constraints. In this paper we show that hard RCPSPs can be efficiently tackled by a portfolio approach that combines the strengths of different constraint solvers Our approach seeks to predict and run in parallel the best solvers for a new, unseen RCPSP instance by enabling the bound communication between them. This on-average allows to outperform the oracle solver that always chooses the best available solver for any given instance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.