Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Integer and combinatorial optimization
Integer and combinatorial optimization
Semiring-based constraint satisfaction and optimization
Journal of the ACM (JACM)
Towards a universal test suite for combinatorial auction algorithms
Proceedings of the 2nd ACM conference on Electronic commerce
Earth Observation Satellite Management
Constraints
AND/OR search spaces for graphical models
Artificial Intelligence
Memory intensive branch-and-bound search for graphical models
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
A BDD-based polytime algorithm for cost-bounded interactive configuration
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Best-first AND/OR search for graphical models
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Taking advantage of stable sets of variables in constraint satisfaction problems
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
AND/OR branch-and-bound for graphical models
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A complexity analysis of space-bounded learning algorithms for the constraint satisfaction problem
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Compiling constraint networks into AND/OR multi-valued decision diagrams (AOMDDs)
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
AND/OR branch-and-bound search for pure 0/1 integer linear programming problems
CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
AND/OR Multi-valued Decision Diagrams for Constraint Networks
Concurrency, Graphs and Models
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We propose a new top down search-based algorithm for compiling AND/OR Multi-Valued Decision Diagrams (AOMDDs), as representations of the optimal set of solutions for constraint optimization problems. The approach is based on AND/OR search spaces for graphical models, state-of-the-art AND/OR Branch-and-Bound search, and on decision diagrams reduction techniques. We extend earlier work on AOMDDs by considering general weighted graphs based on cost functions rather than constraints. An extensive experimental evaluation proves the efficiency of the weighted AOMDD data structure.