TY - JOUR
T1 - Optimal ordering of independent tests with precedence constraints
AU - Berend, D.
AU - Brafman, R.
AU - Cohen, S.
AU - Shimony, S. E.
AU - Zucker, S.
N1 - Funding Information:
Ronen Brafman and Solomon E. Shimony were partially supported by the IMG4 consortium, under a MAGNET grant of the Israeli ministry of trade and industry. The latter is also partially supported by ISF grant number 305/09 .
PY - 2014/1/10
Y1 - 2014/1/10
N2 - We consider scenarios in which a sequence of tests is to be applied to an object; the result of a test may be that a decision (such as the classification of the object) can be made without running additional tests. Thus, one seeks an ordering of the tests that is optimal in some sense, such as minimum expected resource consumption. Sequences of tests are commonly used in computer vision (Paul A. Viola and Michael J. Jones (2001) [15]) and other applications. Finding an optimal ordering is easy when the tests are completely independent. Introducing precedence constraints, we show that the optimization problem becomes NP-hard when the constraints are given by means of a general partial order. Restrictions of the constraints to non-trivial special cases that allow for low-order polynomial-time algorithms are examined.
AB - We consider scenarios in which a sequence of tests is to be applied to an object; the result of a test may be that a decision (such as the classification of the object) can be made without running additional tests. Thus, one seeks an ordering of the tests that is optimal in some sense, such as minimum expected resource consumption. Sequences of tests are commonly used in computer vision (Paul A. Viola and Michael J. Jones (2001) [15]) and other applications. Finding an optimal ordering is easy when the tests are completely independent. Introducing precedence constraints, we show that the optimization problem becomes NP-hard when the constraints are given by means of a general partial order. Restrictions of the constraints to non-trivial special cases that allow for low-order polynomial-time algorithms are examined.
KW - Complexity of ordering problems
KW - Constrained optimization
KW - Test ordering
UR - http://www.scopus.com/inward/record.url?scp=84888000713&partnerID=8YFLogxK
U2 - 10.1016/j.dam.2013.07.014
DO - 10.1016/j.dam.2013.07.014
M3 - Article
AN - SCOPUS:84888000713
SN - 0166-218X
VL - 162
SP - 115
EP - 127
JO - Discrete Applied Mathematics
JF - Discrete Applied Mathematics
ER -