We survey some recent developments in the area of semidefinite optimization applied to integer programming. After recalling some generic modeling techniques to obtain semidefinite relaxations for NP-hard problems, we look at the theoretical power of semidefinite optimization in the context of the Max-Cut and the Coloring Problem. In the second part, we consider algorithmic questions related to semidefinite optimization, and point to some recent ideas to handle large scale problems. The survey is concluded with some more advanced modeling techniques, based on matrix relaxations leading to copositive matrices. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Rendl, F. (2010). Semidefinite relaxations for integer programming. In 50 Years of Integer Programming 1958-2008: From the Early Years to the State-of-the-Art (pp. 687–726). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-68279-0_18
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