Parallel Semidefinite Programming and Combinatorial Optimization
|Title||Parallel Semidefinite Programming and Combinatorial Optimization|
|Year of Publication||2005|
The use of semidefinite programming in combinatorial optimization continues to grow. This growth can be attributed to at least three factors: new semidefinite relaxations that provide tractable bounds to hard combinatorial problems, algorithmic advances in the solution of semidefinite programs (SDP), and the emergence of parallel computing.