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An optimal k-consistency algorithm
Artificial Intelligence
Dynamic Programming and Strong Bounds for the 0-1 Knapsack Problem
Management Science
Where are the hard knapsack problems?
Computers and Operations Research
Depth-bounded discrepancy search
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
A search-infer-and-relax framework for integrating solution methods
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
The power of semidefinite programming relaxations for MAX-SAT
CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a value selection heuristic makes a correct prediction. We provide an extensive empirical evaluation of value selection heuristics for knapsack problems. We investigate how the accuracy of search heuristics varies as a function of depth in the search-tree, and how the accuracies of heuristic predictions are affected by the relative strength of inference methods like pruning and constraint propagation.