Servizi per la didattica

PORTALE DELLA DIDATTICA

01RLDPH

A.A. 2019/20

Course Language

English

Course degree

Master of science-level of the Bologna process in Engineering And Management - Torino

Course structure

Teaching | Hours |
---|---|

Lezioni | 50 |

Esercitazioni in aula | 30 |

Teachers

Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
---|---|---|---|---|---|---|---|

Della Croce Di Dojola Federico | Professore Ordinario | MAT/09 | 20 | 10 | 0 | 0 | 4 |

Teaching assistant

Context

SSD | CFU | Activities | Area context |
---|---|---|---|

MAT/09 | 8 | D - A scelta dello studente | A scelta dello studente |

2018/19

Quantitative methods seek in building up rational models for the representation of complex problems and in devising the related solution algorithms. Objective of the course is to deepen the student skills on several major topics of operations research with emphasis on computational complexity, combinatorial optimization and multi-criteria analysis.

Quantitative methods seek in building up rational models for the representation of complex problems and in devising the related solution algorithms. Objective of the course is to deepen the student skills on several major topics of operations research with emphasis on computational complexity, combinatorial optimization and multi-criteria analysis.

At the end of the course the student must be able to determine the computational complexity of given algorithms, to design exact and heuristic algorithms for real world combinatorial optimization problem, to know methods of multi-criteria analysis and use them in relation to specific decision problem situations.

At the end of the course the student must be able to determine the computational complexity of given algorithms, to design exact and heuristic algorithms for real world combinatorial optimization problem, to know methods of multi-criteria analysis and use them in relation to specific decision problem situations.

Bases of operations research with emphasis on linear programming.

Bases of operations research with emphasis on linear programming.

Computational complexity.
Elements of graph theory.
Combinatorial optimization: exact methods, heuristic approaches, approximation algorithms.
Multi-criteria analysis: introduction to multiobjective optimization (pareto-optimality, solution approaches) and to multicriteria outranking methods, ELECTRE methods for sorting decision problems.

Computational complexity.
Elements of graph theory.
Combinatorial optimization: exact methods, heuristic approaches, approximation algorithms.
Multi-criteria analysis: introduction to multiobjective optimization (pareto-optimality, solution approaches) and to multicriteria outranking methods, ELECTRE methods for sorting decision problems.

The exercise classes are related to the topics presented in the course. In the laboratories commercial software tools are used to deal with more complex problems.

The exercise classes are related to the topics presented in the course. In the laboratories commercial software tools are used to deal with more complex problems.

Slides will be provided directly by the teacher.
Reference textbooks that contain part of the topics presented in the course are among others
• M.R. Garey, D.S. Johnson (1979), Computers and Intractability: A Guide to the Theory of NP-Completeness, W. H. Freeman and Co.
• C.H. Papadimitriou, K. Steiglitz (1982), Combinatorial Optimization. Algorithms and Complexity, Prentice Hall.
• V. Vazirani (2001), Approximation Algorithms, Springer.
• P. Vincke (1992), Multicriteria decision-Aid, Wiley, Chichester.
• L.A. Wolsey (1999), Integer Programming and Combinatorial Optimization, Wiley.

Slides will be provided directly by the teacher.
Reference textbooks that contain part of the topics presented in the course are among others
• M.R. Garey, D.S. Johnson (1979), Computers and Intractability: A Guide to the Theory of NP-Completeness, W. H. Freeman and Co.
• C.H. Papadimitriou, K. Steiglitz (1982), Combinatorial Optimization. Algorithms and Complexity, Prentice Hall.
• V. Vazirani (2001), Approximation Algorithms, Springer.
• P. Vincke (1992), Multicriteria decision-Aid, Wiley, Chichester.
• L.A. Wolsey (1999), Integer Programming and Combinatorial Optimization, Wiley.

Written exam.

Written exam.

© Politecnico di Torino

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY