Lectures related to Exact methods: Gomory cuts

Cutset Formulation: MST Problem

Explores the cutset formulation for the MST Problem and Gomory Cutting Planes method.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Optimal Decision Making: Sensitivity Analysis

Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.

Optimization Problems: Path Finding and Portfolio Allocation

Covers optimization problems in path finding and portfolio allocation.

Linear Programming: Weighted Bipartite Matching

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.

Local Sensitivity Analysis: Feasibility and Optimality

Explores local sensitivity analysis in linear programming, examining how changes impact optimality and feasibility.

Hedging for LPs

Covers the concept of hedging for Linear Programs and the simplex method, focusing on minimizing costs and finding optimal solutions.

Integer Programs: Optimization and Constraints

Explores integer programs, nonconvex optimization, constraints, and geometric aspects of linear programming for optimal solutions.

Simplex Algorithm: Exercises & Interpretation

Covers exercises on the Simplex Algorithm, optimizing solutions subject to linear constraints.

Semi-Definite Programming

Covers semi-definite programming and optimization over positive semidefinite cones.

Simplex Algorithm: Tableau

Covers the main idea behind the Simplex algorithm and explains the Tableau method for solving linear programming problems.

Linear Programming: Two-phase Simplex Algorithm

Covers the application of the two-phase Simplex algorithm to solve linear programming problems.

Optimal Decision Making: Integer Programming

Covers integer programming, convex hulls, Gomory cutting planes, and branch and bound methods.

Linear Programming: Solving LPs

Covers the process of solving Linear Programs (LPs) using the simplex method.

Linear Programming Basics

Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.

Simplex Algorithm: Basics

Introduces the Simplex algorithm for solving flow problems and handling negative cost cycles.

Optimisation Problem: Solving by FM

Covers the modelling and optimization of energy systems, focusing on solving optimization problems with constraints and variables.

Integer Programming Basics

Introduces the basics of integer programming, including binary integer programs and constraint strategies.

Iterative Rounding Heuristic

Explores optimal integer programming, Gomory cuts, and an iterative rounding heuristic.

Linear Optimization: Auxiliary Problem

Explores the formulation of the auxiliary problem in linear optimization and its role in optimal decision-making.