Subject: ALGORITMI DI OTTIMIZZAZIONE (A.A. 2020/2021)
Unit Algoritmi di ottimizzazione
Related or Additional Studies (lesson)
To develop capability of solving complex problems by means of some of the most updated and effective exact and heuristic techniques: namely column generation, decomposition, metaeuristic.
Introduce to the main mathematical/algorithmic methods to deal with computationally challenging problems.
Develop the capability of implementing algorithms to solve complex problems.
Basics of linear and integer programming.
Basics of programming languages.
Exact methods: column generation and Dantzg decomposition (hint )
Overview of Metaheursitic algorithms
Examples of mathematical modelling in python
Examples of applications
Seminars, laboratory, project design in small groups
The final examination consists in two parts: the design and implementation of a project dealing with an optimization problem; (80%) and in a discussion/written assesmnet on the main theoretical aspects presented during the course (20%).
Capability of designing a model for a complex problem.
Capability of choosing a proper algorithm and method to solve a complex problem
Capability of setting up a project for the development of a solution method for an optimization problem
"Column Generation", Desaulniers, Guy, Desrosiers, Jacques, Solomon, Marius M. (Eds.) , Springer
Martin, Richard Kipp (1999), "Large Scale Linear and Integer Optimization: A Unified Approach", Springer
Ronald L. Rardin (2017, second ed.), "Optimization in Operations Research", Pearson.
Gurobi Reference manual
XPRess Reference Manual