Formulate linear and integer programming problems for solving commonly encountered optimization problems. Understand how approximation algorithms compute solutions that are guaranteed to be within ...

Create divide and conquer, dynamic programming, and greedy algorithms. Understand intractable problems, P vs NP and the use of integer programming solvers to tackle some of these problems.

A team of engineers at AI inference technology company BitEnergy AI reports a method to reduce the energy needs of AI applications by 95%. The group has published a paper describing their new ...

MG4C6.2 Mathematical Programming: Introduction to theory and the solution of linear and nonlinear programming problems: basic solutions and the simplex method, convex programming and KKT conditions, ...

Introduction to theory and the solution of linear and nonlinear programming problems: including linear programming, duality, the simplex method, lagrangian duality, convex programming and KKT ...

AI engineers develop an algorithm that will replace floating-point multiplication with integer addition to make AI processing more efficient.

They will learn the foundations of integer and combinatorial optimization, and apply polyhedral theory to design effective algorithms to solve large-scale integer programs in practice.

Description: An advanced course on theory and algorithms for integer and mixed integer optimization problems. Convergence of integer programming algorithms, dual relaxations, Benders decomposition, ...