Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Improving repair-based constraint satisfaction methods by value propagation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Weak-commitment search for solving constraint satisfaction problems
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
The hazards of fancy backtracking
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
New methods to color the vertices of a graph
Communications of the ACM
Graph Coloring with Adaptive Evolutionary Algorithms
Journal of Heuristics
Combining local search and look-ahead for scheduling and constraint satisfaction problems
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Journal of Artificial Intelligence Research
Combining local search and backtracking techniques for constraint satisfaction
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
SAT problems with chains of dependent variables
Discrete Applied Mathematics - The renesse issue on satisfiability
Generalised graph colouring by a hybrid of local search and constraint programming
Discrete Applied Mathematics
A local search algorithm for balanced incomplete block designs
ERCIM'02/CologNet'02 Proceedings of the 2002 Joint ERCIM/CologNet international conference on Constraint solving and constraint logic programming
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Two contrasting search paradigms for solving combinatorial problems are isystematic backtracking and ilocal search. The former is often effective on highly structured problems because of its ability to exploit consistency techniques, while the latter tends to scale better on very large problems. Neither approach is ideal for all problems, and a current trend in artificial intelligence is the hybridisation of search techniques. This paper describes a use of forward checking in local search: pruning coloration neighbourhoods for graph colouring. The approach is evaluated on standard benchmarks and compared with several other algorithms. Good results are obtained; in particular, one variant finds improved colourings on geometric graphs, while another is very effective on equipartite graphs. Its application to other combinatorial problems is discussed.