Conference Proceedings
Parallelizing Constraint Solvers for Hard RCPSP Instances
Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro, P Festa (ed.), M Sellmann (ed.), J Vanschoren (ed.)
Proceedings of the 10th International Conference on Learning and Intelligent Optimization (LION) | SPRINGER INTERNATIONAL PUBLISHING AG | Published : 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.
Grants
Awarded by EU
Funding Acknowledgements
Supported by the EU project FP7-644298 HyVar: Scalable Hybrid Variability for Distributed, Evolving Software Systems.