Complements of Operational Research

Year
1
Academic year
2023-2024
Code
02031266
Subject Area
Industrial Engineering
Language of Instruction
Portuguese
Mode of Delivery
Face-to-face
Duration
SEMESTRIAL
ECTS Credits
6.0
Type
Compulsory
Level
2nd Cycle Studies - Mestrado

Recommended Prerequisites

Linear Algebra, Calculus, Fundamentals of Operational Research.

Teaching Methods

Theoretical and methodological concepts are presented in tutorial lectures, being motivated by real-world problems and illustrated with application examples.

Software (commercial and public domain) packages are used to obtain solutions to the mathematical models, thus freeing the students for the more creative tasks of problem formulation, model building and critical analysis of results.

Assignments will be offered, involving the development of mathematical models for a real-world problem and the generation of the optimal solutions.

Grading:

  -  3 assignments [5/20]

  - Exam [15/20]

Learning Outcomes

Providing the students with methodological and application competences in the context of optimization in engineering problems, enlarging the range of problems addressed in Fundamentals of Operational Research, in particular by considering integer variables and multiple objective functions in optimization problems. Besides, meta-heuristic approaches are introduced to deal with complex optimization problems of combinatorial nature.

Work Placement(s)

No

Syllabus

1. Integer programming (I). Applications of IP. IP models. Use of binary variables in mathematical programming models. Methods to solve IP problems. The "branch-and-bound" algorithm. IP with binary variables. The Balas’ algorithm. The 0-1 knapsack problem. Problem reformulation. Stability of the optimal solution in IP models.

2. Multi-objective linear programming. Revisiting the goal programming model. Strictly and weakly  non-dominated solutions. Scalarization processes. Interactive methods. The STEM method.

3. Meta-heuristics in optimization problems. Tabu search. Simulated annealing. Genetic algorithms. Main steps of a genetic algorithm. Genetic operators. Particle swarm optimization. Differential evolution.

Head Lecturer(s)

Carlos Alberto Henggeler de Carvalho Antunes

Assessment Methods

Assessment
Synthesis work: 25.0%
Exam: 75.0%

Bibliography

- Hillier, F. S., G. J. Lieberman. "Introduction to Operations Research", McGraw-Hill, 2005 (8th ed.).

- Bronson, R., G. Naadimuthu. "Investigação Operacional", Colecção Schaum (2ª. Ed.), McGraw-Hill Portugal, 2001.

- Clímaco, J., C. H.Antunes, M. J. Alves. "Programação Linear Multiobjectivo", Imprensa da Universidade de Coimbra, 2003.

- Michalewicz, Z. e D. B. Fogel. "How to Solve It: Modern Heuristics", Springer, 2002.

- Gaspar-Cunha, A., R. Takahashi, C. H. Antunes (Coord.), „Manual de Computação Evolutiva e Meta-heurística“, Imprensa da Universidade de Coimbra, 2012.

- Chang, Y.L. "WinQSB, Decision Support Software for M/OM (ver 2.0)", Wiley, 2003.

- Antunes, C. H., L. V. Tavares (Coord.). "Casos de Aplicação da Investigação Operacional", McGraw-Hill, 2000.