@inproceedings{3f81f632e5f24f5cb2a876bc36fa58a7,
title = "Parallelizing constraint solvers for hard RCPSP instances",
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.",
author = "Roberto Amadini and Maurizio Gabbrielli and Jacopo Mauro",
year = "2016",
month = jan,
day = "1",
doi = "10.1007/978-3-319-50349-3_16",
language = "English",
isbn = "9783319503486",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "227--233",
editor = "Paola Festa and Meinolf Sellmann and Joaquin Vanschoren",
booktitle = "Learning and Intelligent Optimization - 10th International Conference, LION 10, Revised Selected Papers",
address = "Germany",
note = "10th International Conference on Learning and Intelligent Optimization, LION 10 ; Conference date: 29-05-2016 Through 01-06-2016",
}