Copositive and semidefinite relaxations of the quadratic assignment problem
Semidefinite relaxations of the quadratic assignment problem (QAP) have recently turned out to provide good approximations to the optimal value of QAP. We take a systematic look at various conic relaxations of QAP. We first show that QAP can equivalently be formulated as a linear program over the cone of completely positive matrices. Since it is hard to optimize over this cone, we also look at tractable approximations and compare with several relaxations from the literature. We show that several of the well-studied models are in fact equivalent. It is still a challenging task to solve the strongest of these models to reasonable accuracy on instances of moderate size.
2009
2015-07-10 15:08:22
1033
matematično programiranje, problem kvadratičnega prirejanja, kopozitivno programiranje, semidefinitna poenostavitev, quadratic assignment problem, copositive programming, semidefinite relaxations, lift-and-project relaxations,
r6
Janez
Povh
70
Franz
Rendl
70
UDK
4
519.85
OceCobissID
13
513620761
COBISS_ID
3
15143001
ISSN pri članku
9
1572-5286
NUK URN
18
URN:SI:UM:DK:FCHQ0ZVW
0
Predstavitvena datoteka
2015-07-10 15:08:22