Designing high-quality approximation algorithms for combinatorial optimization problems
For NP-hard combinatorial optimization problems, approximation algorithms with high performances have been proposed. In many of these algorithms, mathematical programming techniques have been used and proved to be very useful. In this survey, we present recent mathematical programming techniques as well as classic fundamental techniques, by showing how these techniques are used in designing high-quality approximation algorithms for NP-hard combinatorial optimization problems.
dynamic programming linear programming relaxation primal dual method scaling semidefinite programming