The book presents a graduate level, rigorous, and self-contained introduction to linear optimization (LO), the presented topics being - expressive abilities of LO;
- geometry of LO — structure of polyhedral sets, LO duality and its applications;
- traditional LO algorithms — primal and dual simplex methods, and network simplex method;
- polynomial time solvability of LO via ellipsoid algorithm;
- conic programming with emphasis on expressing abilities of second order and semidefinite optimization, and polynomial time primal-dual interior point algorithms for linear and semidefinite optimization.
The book presents a graduate level, rigorous, and self-contained introduction to linear optimization (LO), the presented topics being
expressive abilities of LO;
geometry of LO — structure of polyhedral sets, LO duality and its applications;
traditional LO algorithms — primal and dual simplex me...