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OPERATIONS RESEARCH

## OVERVIEW

## AIMS AND CONTENT

### LEARNING OUTCOMES

### AIMS AND LEARNING OUTCOMES

### PREREQUISITES

### TEACHING METHODS

### SYLLABUS/CONTENT

### RECOMMENDED READING/BIBLIOGRAPHY

## TEACHERS AND EXAM BOARD

### Exam Board

## LESSONS

### TEACHING METHODS

### LESSONS START

### Class schedule

## EXAMS

### EXAM DESCRIPTION

### ASSESSMENT METHODS

### Exam schedule

### FURTHER INFORMATION

CODE | 80155 |
---|---|

ACADEMIC YEAR | 2020/2021 |

CREDITS |
9 credits during the 1st year of 11160 COMPUTER ENGINEERING (LM-32) GENOVA
7 credits during the 3nd year of 8760 Mathematics (L-35) GENOVA 7 credits during the 1st year of 9011 Mathematics (LM-40) GENOVA |

SCIENTIFIC DISCIPLINARY SECTOR | MAT/09 |

LANGUAGE | English |

TEACHING LOCATION | GENOVA (COMPUTER ENGINEERING ) |

SEMESTER | 1° Semester |

TEACHING MATERIALS | AULAWEB |

The Course introduces to optimization models and methods for the solution of decision problems. It is structured according to the basic topics of problem modelling, its tractability, and its solution by means of algorithms that can be implemented on computers. Case studies from Engineering, with particular attention to Information Technology, are presented and investigated.

The Course introduces to optimization models and methods for the solution of decision problems. It is structured in the main topics of problem modelling, computational tractability, and solution by means of algorithms that can be implemented on a computer. Several applications are considered and various case studies are detailed. The target of the Course consists in making the students acquire the expertise to face decision problems by means of models and methods that can operate in the presence of limited resources. The students will be taught to: understanding and modelling a decision process in terms of an optimization problem by defining the decision variables, the cost function to be minimized (or the figure of merit to be maximized), and the constraints; framing the obtained problem within the range of the reference optimization problems (linear/nonlinear, discrete/continuous, deterministic/stochastic, static/dynamic, etc); achieving the matching between the corresponding solving algorithm and a suitable software.

The students will be taught to:

- interpret and shape a decision-making process in terms of an optimization problem, identifying the decision-making variables, the cost function to minimize (or the figure of merit to maximize), and the constraints;

- framing the problem in the range of problems considered "canonical" (linear / nonlinear, discrete / continuous, deterministic / stochastic, static / dynamic, etc.);

- realizing the "matching" between the solving algorithm (to choose from existing or to be designed) and an appropriate processing software support.

Linear Algebra. Vector and matrix calculus. Basic concepts of Mathematical Analysis and Geometry.

Lectures and exercises.

INTRODUCTION TO OPERATIONS RESEARCH

LINEAR PROGRAMMING

DUALITY

INTEGER PROGRAMMING

GRAPH AND NETWORK OPTIMIZATION

COMPLEXITY THEORY

NONLINEAR PROGRAMMING

DYNAMIC PROGRAMMING

CASE STUDIES FROM INFORMATION TECHNOLOGY

SOFTWARE TOOLS FOR OPTIMIZATION

Lecture notes provided by the teacher and available in electronic format.

**Office hours:** By appointment.

MARCELLO SANGUINETI (President)

MAURO GAGGERO

DANILO MACCIO'

MASSIMO PAOLUCCI (President Substitute)

Lectures and exercises.

September 21, 2020.

All class schedules are posted on the EasyAcademy portal.

Written, if it will be possible to make exams "in presence". Otherwise, the teacher will decide whether the exam via Teams will be written or oral.

Comprehension of the concepts explained during the Course.

Capability to:

- interpret and shape a decision-making process in terms of an optimization problem, identifying the decision-making variables, the cost function to minimize (or the figure of merit to maximize), and the constraints;

- frame the problem in the range of problems considered "canonical" (linear / nonlinear, discrete / continuous, deterministic / stochastic, static / dynamic, etc.);

- choose and/or develop a solving algorithm and apply it to solve the problem.

Date | Time | Location | Type | Notes |
---|---|---|---|---|

07/01/2021 | 09:00 | GENOVA | Scritto | |

04/02/2021 | 09:00 | GENOVA | Scritto | |

08/06/2021 | 09:00 | GENOVA | Scritto | |

29/06/2021 | 09:00 | GENOVA | Scritto | |

09/09/2021 | 09:00 | GENOVA | Scritto |

For the Laurea in Mathematics, which "borrows" only 7 cfu, the following topics are excluded:

DYNAMIC PROGRAMMING

CASE STUDIES FROM INFORMATION TECHNOLOGY