Title :
Extending GENET with lazy arc consistency
Author :
Stuckey, Peter J. ; Tam, Vincent
Author_Institution :
Dept. of Comput. Sci., Melbourne Univ., Parkville, Vic., Australia
fDate :
9/1/1998 12:00:00 AM
Abstract :
Many important applications, such as graph coloring, scheduling and production planning, can be solved by GENET, a local search method which is used to solve binary constraint satisfaction problems (CSPs). Where complete search methods are typically augmented with consistency methods to reduce the search, local search methods are not. We propose a consistency technique, lazy arc consistency, which is suitable for use within GENET. We show it can improve the efficiency of the GENET search on some instances of binary CSPs, and does not suffer the overhead of full arc consistency
Keywords :
computational complexity; constraint theory; graph colouring; logic programming; neural nets; search problems; GENET local search method; binary constraint satisfaction problems; consistency technique; graph coloring; lazy arc consistency; production planning; scheduling; Algorithm design and analysis; Artificial neural networks; Convergence; Evolutionary computation; Job shop scheduling; Logic programming; Microprogramming; Production planning; Search methods; Simulated annealing;
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
DOI :
10.1109/3468.709620