10381 - Optimization Algorithms

Course Unit Page

Academic Year 2018/2019

Learning outcomes

The student will be capable of defining logic and mathematical model of optimization and decision problems by using mathematical programming and graph theory. Can analyze the complexity of computational problems and characterize their difficulty. Can define also using computer codes and software the solution of some classes of problems. Can write technical reports.

Course contents

Optimization and decision models. Mathematical Models of optimization problems. Algorithms and computational complexity. Fundamental data structures for optimization problems. Assignment, covering and facility location problems. Heuristics algorithms. Integer programming models and solution through professional solvers.

Readings/Bibliography

Slides of the lectures

Teaching methods

Frontal lectures, exercises and some labs exercises

Assessment methods

The assessment of learning is based on a oral and a written examination, each covering the whole course.

Teaching tools

Public domain solvers

Office hours

See the website of Roberto Baldacci