Presents recent advances in the mathematical theory of discrete optimization, particularly those supported by methods from algebraic geometry, commutative algebra, convex and discrete geometry, generating functions, and other tools normally considered outside the standard curriculum in optimization.Algebraic and Geometric Ideas in the Theory of Discrete Optimization:Offers several research technologies not yet well known among practitioners of discrete optimizationnMinimizes prerequisites for learning these methods. Provides a transition from linear discrete optimization to nonlinear discrete optimization.Offers several research technologies not yet well known among practitioners of discrete optimization, minimizes prerequisites for learning these methods, and provides a transition from linear discrete optimization to nonlinear discrete optimization.
