Parallelizing constraint solvers for hard RCPSP instances

Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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.

Original languageEnglish
Title of host publicationLearning and Intelligent Optimization - 10th International Conference, LION 10, Revised Selected Papers
EditorsPaola Festa, Meinolf Sellmann, Joaquin Vanschoren
Number of pages7
PublisherSpringer
Publication date1. Jan 2016
Pages227-233
ISBN (Print)9783319503486
DOIs
Publication statusPublished - 1. Jan 2016
Externally publishedYes
Event10th International Conference on Learning and Intelligent Optimization, LION 10 - Ischia, Italy
Duration: 29. May 20161. Jun 2016

Conference

Conference10th International Conference on Learning and Intelligent Optimization, LION 10
Country/TerritoryItaly
CityIschia
Period29/05/201601/06/2016
SeriesLecture Notes in Computer Science
Volume10079 LNCS
ISSN0302-9743

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