TY - GEN
T1 - Conflict directed backjumping for max-CSPs
AU - Zivan, Roie
AU - Meisels, Amnon
PY - 2006
Y1 - 2006
N2 - Constraint Optimization problems are commonly solved using a Branch and Bound algorithm enhanced by consistency maintenance procedures (Wallace and Freuder 1993; Larrosa and Meseguer 1996; Larrosa et al. 1999; Larrosa and Schiex 2003; 2004). All these algorithms traverse the search space in a chronological order and gain their efficiency from the quality of the consistency maintenance procedure. The present study introduces Conflict-directed Backjumping (CBJ) for Branch and Bound algorithms. The proposed algorithm maintains Conflict Sets which include only assignments whose replacement can lead to a better solution. The algorithm backtracks according to these sets. CBJ can be added to all classes of the Branch and Bound algorithm. In particular to versions of Branch & Bound that use advanced maintenance procedures of soft local consistency levels, NC*, AC* and FDAC (Larrosa and Schiex 2003; 2004). The experimental evaluation of B&B_CBJ on random Max-CSPs shows that the performance of all algorithms is improved both in the number of assignments and in the time for completion.
AB - Constraint Optimization problems are commonly solved using a Branch and Bound algorithm enhanced by consistency maintenance procedures (Wallace and Freuder 1993; Larrosa and Meseguer 1996; Larrosa et al. 1999; Larrosa and Schiex 2003; 2004). All these algorithms traverse the search space in a chronological order and gain their efficiency from the quality of the consistency maintenance procedure. The present study introduces Conflict-directed Backjumping (CBJ) for Branch and Bound algorithms. The proposed algorithm maintains Conflict Sets which include only assignments whose replacement can lead to a better solution. The algorithm backtracks according to these sets. CBJ can be added to all classes of the Branch and Bound algorithm. In particular to versions of Branch & Bound that use advanced maintenance procedures of soft local consistency levels, NC*, AC* and FDAC (Larrosa and Schiex 2003; 2004). The experimental evaluation of B&B_CBJ on random Max-CSPs shows that the performance of all algorithms is improved both in the number of assignments and in the time for completion.
UR - http://www.scopus.com/inward/record.url?scp=33846016986&partnerID=8YFLogxK
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AN - SCOPUS:33846016986
SN - 1577352904
SN - 9781577352907
T3 - AAAI Workshop - Technical Report
SP - 71
EP - 78
BT - Heuristic Search, Memory-Based Heuristics and their Applications - Papers from the AAAI Workshop, Technical Report
T2 - 2006 AAAI Workshop
Y2 - 16 July 2006 through 17 July 2006
ER -