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Hybrid Metaheuristics for Stochastic Constraint Programming

Authors: 

Steven Prestwich, Armagan Tarim, Roberto Rossi, Brahim Hnich

Publication Type: 
Refereed Original Article
Abstract: 
Stochastic Constraint Programming (SCP) is an extension of Constraint Programming for modelling and solving combinatorial problems involving uncertainty. This paper proposes a metaheuristic approach to SCP that can scale up to large problems better than state-of-the-art complete methods, and exploits standard filtering algorithms to handle hard constraints more efficiently. For problems with many scenarios it can be combined with scenario reduction and sampling methods.
Digital Object Identifer (DOI): 
10.1007/s10601-014-9170-x
Publication Status: 
Published
Publication Date: 
01/09/2014
Journal: 
Constraints
Volume: 
20
Issue: 
1
Pages: 
57-76
Institution: 
National University of Ireland, Cork (UCC)
Project Acknowledges: 
Open access repository: 
Yes