Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Tree clustering for constraint networks (research note)
Artificial Intelligence
Encodings of non-binary constraint satisfaction problems
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
A Dual Graph Translation of a Problem in 'Life'
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Binary encodings of non-binary constraint satisfaction problems: algorithms and experimental results
Journal of Artificial Intelligence Research
Search Space Reduction for Constraint Optimization Problems
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Solving generalized optimization problems subject to SMT constraints
FAW-AAIM'12 Proceedings of the 6th international Frontiers in Algorithmics, and Proceedings of the 8th international conference on Algorithmic Aspects in Information and Management
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In a constraint optimization problem (COP), many feasible valuations lead to the same objective value. This often means a huge search space and poor performance in the propagation between the objective and problem variables. In this paper, we propose a different modeling and search strategy which focuses on the cost function. We show that by constructing a dual model on the objective variables, we can get strong propagalion between the objective variables and the problem variables which allows search on the objective variables. We explain why and when searching on the objective variables can lead to large gains. We present a new Russian Doll Search algorithm, ORDS, which works on objective variables with dynamic variable ordering. Finally, we demonstrate using the hard Still-Life optimization problem the benefits of changing to the objective function model and ORDS.