Lectures in course MGT-483: Optimal decision making

Linear Equations: Solutions and Intervals

Covers the solution of linear equations and the linearity of functions.

Mixed-Integer Linear Programming: Formulations and Applications

Explores mixed-integer linear programming, binary variables, 0-1 knapsack, assignment problems, and LP relaxation strength.

Solving Integer Linear Programs

Covers solving integer linear programs graphically, algorithmically, and through optimization methods.

Spanning Trees: Definition and Applications

Introduces spanning trees in graphs and the Minimum Spanning Tree problem, exploring efficient algorithms for optimal decision-making.

Branch & Bound: Optimization

Covers the Branch & Bound algorithm for efficient exploration of feasible solutions and discusses LP relaxation, portfolio optimization, Nonlinear Programming, and various optimization problems.

Convex Optimization: Theory and Applications

Explores convex optimization theory, covering local and global minima, convex functions, and applications in various fields.

Linear Programming: Convex Hull

Covers MAE regression, convex hull, reformulation advantages, and practical problems with decision variables and constraints.