TY - JOUR
T1 - Scheme for unifying optimization and constraint satisfaction methods
AU - Hooker, John
AU - Ottosson, Greger
AU - Thorsteinsson, Erlender S.
AU - Kim, Hak Jin
PY - 2000/3
Y1 - 2000/3
N2 - Optimization and constraint satisfaction methods are complementary to a large extent, and there has been much recent interest in combining them. Yet no generally accepted principle or scheme for their merger has evolved. We propose a scheme based on two fundamental dualities: the duality of search and inference, and the duality of strengthening and relaxation. Optimization as well as constraint satisfaction methods can be seen as exploiting these dualities in their respective ways. Our proposal is that rather than employ either type of method exclusively, one can focus on how these dualities can be exploited in a given problem class. The resulting algorithm is likely to contain elements from both optimization and constraint satisfaction, and perhaps new methods that belong to neither.
AB - Optimization and constraint satisfaction methods are complementary to a large extent, and there has been much recent interest in combining them. Yet no generally accepted principle or scheme for their merger has evolved. We propose a scheme based on two fundamental dualities: the duality of search and inference, and the duality of strengthening and relaxation. Optimization as well as constraint satisfaction methods can be seen as exploiting these dualities in their respective ways. Our proposal is that rather than employ either type of method exclusively, one can focus on how these dualities can be exploited in a given problem class. The resulting algorithm is likely to contain elements from both optimization and constraint satisfaction, and perhaps new methods that belong to neither.
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U2 - 10.1017/S0269888900001077
DO - 10.1017/S0269888900001077
M3 - Article
AN - SCOPUS:0034155409
SN - 0269-8889
VL - 15
SP - 11
EP - 30
JO - Knowledge Engineering Review
JF - Knowledge Engineering Review
IS - 1
ER -