Theory of linear and integer programming
Theory of linear and integer programming
On the minimality and global consistency of row-convex constraint networks
Journal of the ACM (JACM)
Robust and optimal control
The essence of constraint propagation
Theoretical Computer Science
Computing Two-Dimensional Integer Hulls
SIAM Journal on Computing
Combinatorial optimization: current successes and directions for the future
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. IV: optimization and nonlinear equations
MPLS: technology and applications
MPLS: technology and applications
Deriving traffic demands for operational IP networks: methodology and experience
IEEE/ACM Transactions on Networking (TON)
Robust Solutions to Uncertain Semidefinite Programs
SIAM Journal on Optimization
Traffic matrix estimation: existing techniques and new directions
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Interval Constraint Logic Programming
Selected Papers from Constraint Programming: Basics and Trends
Towards Stochastic Constraint Programming: A Study of Online Multi-choice Knapsack with Deadlines
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Beyond NP: Arc-Consistency for Quantified Constraints
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Modeling Camera Control with Constrained Hypertubes
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice
ACM Transactions on Computer Systems (TOCS)
An information-theoretic approach to traffic matrix estimation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Reasoning about Uncertainty
Measuring ISP topologies with rocketfuel
IEEE/ACM Transactions on Networking (TON)
Efficient solving of quantified inequality constraints over the real numbers
ACM Transactions on Computational Logic (TOCL)
Managing restaurant tables using constraints
Knowledge-Based Systems
Regrets only! online stochastic optimization under time constraints
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Scenario-based stochastic constraint programming
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
QCSP-solve: a solver for quantified constraint satisfaction problems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Constructing Uncertainty Sets for Robust Linear Optimization
Operations Research
Mixed constraint satisfaction: a framework for decision problems under incomplete knowledge
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Constraint based resilience analysis
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Localization of an underwater robot using interval constraint propagation
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
A structural characterization of temporal dynamic controllability
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Robust solutions of uncertain linear programs
Operations Research Letters
IP network configuration for intradomain traffic engineering
IEEE Network: The Magazine of Global Internetworking
Set based robust design of mechanical systems using the quantifier constraint satisfaction algorithm
Engineering Applications of Artificial Intelligence
Constraint reasoning with uncertain data using CDF-Intervals
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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Constraint Programming (CP) has proved an effective paradigm to model and solve difficult combinatorial satisfaction and optimization problems from disparate domains. Many such problems arising from the commercial world are permeated by data uncertainty. Existing CP approaches that accommodate uncertainty are less suited to uncertainty arising due to incomplete and erroneous data, because they do not build reliable models and solutions guaranteed to address the user's genuine problem as she perceives it. Other fields such as reliable computation offer combinations of models and associated methods to handle these types of uncertain data, but lack an expressive framework characterizing the resolution methodology independently of the model. We present a unifying framework that extends the CP formalism in both model and solutions, to tackle ill-defined combinatorial problems with incomplete or erroneous data. The certainty closure framework brings together modeling and solving methodologies from different fields into the CP paradigm to provide reliable and efficient approches for uncertain constraint problems. We demonstrate the applicability of the framework on a case study in network diagnosis. We define resolution forms that give generic templates, and their associated operational semantics, to derive practical solution methods for reliable solutions.