Sumários

Lesson 4

5 Fevereiro 2026, 08:00 • Cristina Requejo

  •      Representing LP models: canonical forms and standard form of an LP, reformulation operations.
  •      Some convexity results: convex set, polytope, polyhedron, extreme point, ray, extreme ray.
  • Feasible solution set of an LP model as convex combination of extreme points, and as extreme points and extreme rays.

Lesson 3

3 Fevereiro 2026, 10:00 • Cristina Requejo

·      .   Modeling several examples of LP problems;

. Assumptions of LP.

Lesson 2

29 Janeiro 2026, 08:00 • Cristina Requejo

  • Solving several examples graphically illustrating:
    • Solutions, feasible and infeasible.
    • Feasible region: bounded and unbounded cases.
    • Optimal solutions:
      • unique optimal solution,
      • alternative optimal solutions,
      • problem with unbounded objective value.
  • Solving LP problems using Excel Solver.

Lesson 1

27 Janeiro 2026, 10:00 • Cristina Requejo

Course presentation: syllabus overview, bibliography, and assessment method.

Operational Research (OR): general methodology and decision-making framework.

Models in OR: different types of models and their role in addressing a decision challenge.


1. Introduction to Linear Programming (LP)

·         Formulation of a mathematical programming model.

·         Definition of decision variables, objective function, and constraints.

·         Example with two decision variables.

·         Graphical method for solving an LP problem.

·         Illustrative example.