Boosting set constraint propagation for network design

Authors:
Justin Yip;Pascal Van Hentenryck;Carmen Gervet
Affiliations:
Brown University, Providence, RI;Brown University, Providence, RI;German University in Cairo, New Cairo, Egypt
Venue:
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Year:
2010

Citing 8
Cited 1

Enhanced Model Representations for an Intra-Ring Synchronous Optical Network Design Problem Allowing Demand Splitting

INFORMS Journal on Computing
Improving Discrete Model Representations via Symmetry Considerations

Management Science
Enhancing set constraint solvers with lexicographic bounds

Journal of Heuristics
Length-lex ordering for set CSPs

AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Bound consistency for binary length-lex set constraints

AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Filtering atmost1 on pairs of set variables

CPAIOR'08 Proceedings of the 5th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Symmetry and search in a network design problem

CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Open constraints in a closed world

CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

Exponential propagation for set variables

CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper reconsiders the deployment of synchronous optical networks (SONET), an optimization problem naturally expressed in terms of set variables. Earlier approaches, using either MIP or CP technologies, focused on symmetry breaking, including the use of SBDS, and the design of effective branching strategies. This paper advocates an orthogonal approach and argues that the thrashing behavior experienced in earlier attempts is primarily due to a lack of pruning. It studies how to improve domain filtering by taking a more global view of the application and imposing redundant global constraints. The technical results include novel hardness results, propagation algorithms for global constraints, and inference rules. The paper also evaluates the contributions experimentally by presenting a novel model with static symmetric-breaking constraints and a static variable ordering which is many orders of magnitude faster than existing approaches.