Mathematical Optimization

Learning Goals

The student will learn how to formulating a discrete optimization model to maximize or minimize a function of many variables subject to (i) equality and inequality constraints, and (ii) integrality restrictions on some or all of the variables.

Program in pills

Modeling techniques using integer and continuous variables. Optimality, relaxation, and bounds. Linear programming. Network flow problems. Integer Programming. Combinatorial optimization. Large-scale optimization.

Area

Mathematical and statistical modelling

Curriculum Foundations
TAF Type

D

Curriculum Industry
TAF Type

B

Curriculum Health
TAF Type

D

Curriculum Economy
TAF Type

D

SSD

MAT/09

ECTS

6

Semester

2

Lecturers

Lorenzo Castelli