Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Linear-space best-first search
Artificial Intelligence
Exploiting algebraic structure in parallel state space search
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
The Differencing Method of Set Partitioning
The Differencing Method of Set Partitioning
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
From approximate to optimal solutions: a case study of number partitioning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Annals of Mathematics and Artificial Intelligence
A decomposition-based implementation of search strategies
ACM Transactions on Computational Logic (TOCL)
Enhancing Stochastic Search Performance by Value-Biased Randomization of Heuristics
Journal of Heuristics
Non-wrapping order crossover: an order preserving crossover operator that respects absolute position
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Discrepancy-Based Additive Bounding Procedures
INFORMS Journal on Computing
YIELDS: A Yet Improved Limited Discrepancy Search for CSPs
CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Interleaved depth-first search
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Depth-bounded discrepancy search
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
From approximate to optimal solutions: constructing pruning and propagation rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Incomplete tree search using adaptive probing
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Search spaces for min-perturbation repair
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Parallel machine scheduling with precedence constraints and setup times
Computers and Operations Research
Discrepancy search for the flexible job shop scheduling problem
Computers and Operations Research
Discrepancy-based sliced neighborhood search
AIMSA'10 Proceedings of the 14th international conference on Artificial intelligence: methodology, systems, and applications
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
On-line planning and scheduling: an application to controlling modular printers
Journal of Artificial Intelligence Research
Limited discrepancy search revisited
Journal of Experimental Algorithmics (JEA)
Expert Systems with Applications: An International Journal
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
DR.FILL: crosswords and an implemented solver for singly weighted CSPs
Journal of Artificial Intelligence Research
Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems
Journal of Mathematical Modelling and Algorithms
Improved bounds for hybrid flow shop scheduling with multiprocessor tasks
Computers and Industrial Engineering
Hi-index | 0.00 |
We present an improvement to Harvey and Ginsberg's limited discrepancy search algorithm, which eliminates much of the redundancy in the original, by generating each path from the root to the maximum search depth only once. For a complete binary tree of depth d, this reduces the asymptotic complexity from O(d+2/2 2d) to O(2d). The savings is much less in a partial tree search, or in a heavily pruned tree. The overhead of the improved algorithm on a complete b-ary tree is only a factor of b/(b - 1) compared to depth-first search. While this constant factor is greater on a heavily pruned tree, this improvement makes limited discrepancy search a viable alternative to depth-first search, whenever the entire tree may not be searched. Finally, we present both positive and negative empirical results on the utility oflimited discrepancy search, for the problem of number partitioning.