Description

Theory/Practice
2

Laboratory
2

Instructors

Maria Teresa Pereira

Contents

CP1 ? Mathematical Modelling in Linear Programming
- Formulation of real-world problems as linear mathematical models
- Identification of decision variables, constraints, and objective function
- Classical models: transportation, assignment, inventory management, production, scheduling
- Sensitivity analysis and interpretation of results
 

CP2 ? Linear Programming
- Simplex method: algorithms and economic interpretation
- Duality: dual problem formulation and fundamental theorems
- Sensitivity analysis and post-optimization techniques
 

CP3 ? Topics in Integer Programming
- Pure and mixed integer programming (MILP)
- Problem formulation with binary variables
Solution algorithms: branch and bound, cutting planes
 

CP4 ? Topics in Dynamic Programming
- Bellman?s principle of optimality
- Formulation of sequential decision problems
- Deterministic and stochastic dynamic programming

Learning Outcomes

Enable students to use Operational Research techniques in solving complex problems, including the identification and analysis of alternative decisions.
OB1- Analyse and solve complex problems, including the identification and analysis of alternative decisions;
OB2- Build mathematical programming models;
OB3- Use of Operations Research software to solve complex problems and analysis of solutions.