Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

A.A. 2018/2019

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I semestre Oct 1, 2018 Jan 31, 2019
II semestre Mar 4, 2019 Jun 14, 2019
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2019 Feb 28, 2019
Sessione estiva d'esame Jun 17, 2019 Jul 31, 2019
Sessione autunnale d'esame Sep 2, 2019 Sep 30, 2019
Degree sessions
Session From To
Sessione di laurea estiva Jul 22, 2019 Jul 22, 2019
Sessione di laurea autunnale Oct 15, 2019 Oct 15, 2019
Sessione di laurea autunnale straordinaria Nov 21, 2019 Nov 21, 2019
Sessione di laurea invernale Mar 19, 2020 Mar 19, 2020
Holidays
Period From To
Sospensione attività didattica Nov 2, 2018 Nov 3, 2018
Vacanze di Natale Dec 24, 2018 Jan 6, 2019
Vacanze di Pasqua Apr 19, 2019 Apr 28, 2019
Vacanze estive Aug 5, 2019 Aug 18, 2019

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

A B C D G M O P R S Z

Albi Giacomo

giacomo.albi@univr.it +39 045 802 7913

Angeleri Lidia

lidia.angeleri@univr.it 045 802 7911

Baldo Sisto

sisto.baldo@univr.it 045 802 7935

Bos Leonard Peter

leonardpeter.bos@univr.it +39 045 802 7987

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Caliari Marco

marco.caliari@univr.it +39 045 802 7904

Canevari Giacomo

giacomo.canevari@univr.it +39 045 8027979

Chignola Roberto

roberto.chignola@univr.it 045 802 7953

Cordoni Francesco Giuseppe

francescogiuseppe.cordoni@univr.it

Daffara Claudia

claudia.daffara@univr.it +39 045 802 7942

Daldosso Nicola

nicola.daldosso@univr.it +39 045 8027076 - 7828 (laboratorio)

De Sinopoli Francesco

francesco.desinopoli@univr.it 045 842 5450

Di Persio Luca

luca.dipersio@univr.it +39 045 802 7968

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Magazzini Laura

laura.magazzini@univr.it 045 8028525

Malachini Luigi

luigi.malachini@univr.it 045 8054933

Mantese Francesca

francesca.mantese@univr.it +39 045 802 7978

Mariotto Gino

gino.mariotto@univr.it +39 045 8027031

Mariutti Gianpaolo

gianpaolo.mariutti@univr.it 045 802 8241

Mazzuoccolo Giuseppe

giuseppe.mazzuoccolo@univr.it +39 0458027838

Migliorini Sara

sara.migliorini@univr.it +39 045 802 7908

Orlandi Giandomenico

giandomenico.orlandi at univr.it 045 802 7986

Piccinelli Fabio

fabio.piccinelli@univr.it +39 045 802 7097

Rizzi Romeo

romeo.rizzi@univr.it +39 045 8027088

Sansonetto Nicola

nicola.sansonetto@univr.it 049-8027932

Schuster Peter Michael

peter.schuster@univr.it +39 045 802 7029

Solitro Ugo

ugo.solitro@univr.it +39 045 802 7977

Zuccher Simone

simone.zuccher@univr.it

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University. Please select your Study Plan based on your enrolment year.

CURRICULUM TIPO:
ModulesCreditsTAFSSD
6
A
(MAT/02)
6
B
(MAT/03)
6
C
(SECS-P/01)
6
C
(SECS-P/01)
6
B
(MAT/06)
English B1
6
E
-
ModulesCreditsTAFSSD
6
C
(SECS-P/05)
12
C
(SECS-S/06)
Final exam
6
E
-

2° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
B
(MAT/03)
6
C
(SECS-P/01)
6
C
(SECS-P/01)
6
B
(MAT/06)
English B1
6
E
-

3° Year

ModulesCreditsTAFSSD
6
C
(SECS-P/05)
12
C
(SECS-S/06)
Final exam
6
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
Between the years: 1°- 2°- 3°
Other activities
6
F
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S00001

Teacher

Romeo Rizzi

Coordinatore

Romeo Rizzi

Credits

6

Scientific Disciplinary Sector (SSD)

MAT/09 - OPERATIONS RESEARCH

Language

Italian

Period

II semestre dal Mar 4, 2019 al Jun 14, 2019.

Learning outcomes

The student of mathematics (L40, Verona) will encounter in concrete the concepts of: problems, models, formulations of operations research, but also of instances, algorithms, reductions and mappings among problems of the computer science field. The course will propose some models of operations research, at least the following: linear programming (LP), integer linear programming (ILP), max-flows and min-cuts, bipartite matchings and node covers, minimum spanning trees, shortest paths, Eulerian paths, and some models resorting on dynamic programming among which some knapsack variants. For all these models/problems, except PLI, the student will learn the solving algorithms, the properties on which they hinge, and how to conduct their execution.
However, besides and beyond this, the course aims at building a good and active relationship, practice, and acquaintance, with general mathematical methodologies and techniques (more typical of discrete math and for this reason not yet fully assimilated from our students) and some basic underpinnings of computer science. In particular, we insist on the dialog with problems and with the art/technique of conjecturing, no occasion is lost to spotlight where invariants and monovariants play a role in proofs, algorithms and data structures. We build up confidence with mathematical induction as an active tool for problem solving, and introducing the dialects of induction most voted to efficiency (divide et impera, recursion with memoization, dynamic programming). Some basic principles of informatics are underlined, like coding, algorithms, data structures, recursion as a counterpart of mathematical induction and of computability. (In some editions of the course first scratch introductions to numerability and computability have been offered). Coming to efficiency, our central perspective, the use of asymptotic notation is justified and adopted, the classes P, NP, coNP are introduced, and the concepts of good characterizations, good conjectures and good theorems are illustrated in length and complexity theory is advertised as a lively source of new methodologies in the art of facing problems and enquiry their intrinsic structural properties. Several aspects of the role and importance of the art of reducing one problem to another are discussed and clarified. The life cycle of a good conjecture, the workflow linking good conjectures and algorithms, the production and interpretation of counterexamples as a means of dialog with the problem, and the possible use of them in obtaining NP-completeness proofs, are all discussed, investigated and exemplified in action.
Explicit emphasis is constantly given to the role and use of certificates. Meanwhile these transversal and high competences of methodological interest and imprinting are delivered, the students is asked to learn and develop several concrete procedural competences, in particular within LP, and in an algorithmic treatment of graph theory, introduced as a versatile model and an intuitive and expressive language for the formulation of problems.
For a complete and detailed list of all these procedural competences delivered and requested, see the past exams and corrections over the various editions of the course.

The notions from computational complexity introduced in the course, and the attention to the languages of the certificates, will lead the student to recognize with more awareness the structure of a sound proof.
Dealing with instances, problems, models, both from the perspective of algorithms and of models and formulations, will enforce the attitude and competence in casting simple problems from the applications into mathematical models.
The knowledge of the paradigmatic results of linear programming theory (duality, complementary slackness, economic interpretation, sensitivity analysis) will provide the student with important tools in obtaining non-trivial insights on the practical problem from the model.

Program

Operations Research offers quantitative methods and models for the optimal management of resources, and optimization of profits, services, strategies, procedures.
This course of Operations Research gets to Mathematical Programming
moving from Algorithmics and Computational Complexity.
After revisiting mathematical induction, recursion, divide et impera, with a curiosity driven problem solving approach, we insist on dynamic programming thinking which gets then exemplified in a few classical models of Operations Research and Computational Biology.
With emphasis on method and techniques, we get involved in formulating, encoding and modeling problems, conjecturing about them, reducing one to the other,
and well characterizing them.
The course offers an in-depth introduction to linear programming.
Following the historical path, we introduce graphs as for modeling,
and explore the basic fundamental results in combinatorial optimization and graph theory.

LIST OF TOPICS:

1. Basic Notions
problems
models
algorithms
complexity

2. Introduction to Algorithms and Complexity
analysis of a few algorithms
design techniques (recursion, divede et impera, recursion with memoization, dynamic programming, greedy)
complexity theory (P, NP, co-NP, good characterizations, good conjectures, examples of NP-completeness proofs)

3. Combinatorial Optimization Models
knapsack problems
Problems on sequences
Problems on DAGs

4. Introduction to Graph Theory
graphs and digraphs as models
a few good characterizations (bipartite, Eulerian, acyclic, planar graphs)
a few NP-hard models (Hamilton cycles, cliques, colorability)
shortest paths
minimum spanning trees
maximum flows
bipartite matchings

5. Linear Programming (LP)
the LP and the ILP models (definition, motivations, complexity, role)
geometric method and view (feasibility space,
pivot, duality, dual variables, degeneracy, complementary slackness)
standard and canonical form
simplex method
duality theory
complementary slackness
economic interpretation of the dual variables
sensitivity analysis

BOOKS, NOTES AND OTHER DIDACTIC MATERIALS AND RESOURCES:

At the following page you find a list of available materials (books, notes, videos) about topics covered within the course:

http://profs.sci.univr.it/~rrizzi/classes/RO/materiali

If you find out further effective material help us enlarging this list.

TUTORING (IF AVAILABLE):

For the 2017-18 edition we are planning to introduce a tutor that will assist and guide the students in performing the exercises suggested during the class and in conducting practical experiences.

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
Christos H. Papadimitriou, Kenneth Steiglitz Combinatorial optimization : algorithms and complexity Dover Publications, Inc. 1998 0-486-40258-4
Robert J. Vanderbei Linear Programming: Foundations and Extensions (Edizione 4) Springer 2001 978-1-4614-7630-6

Examination Methods

At the end of the course, a written exam with various types of exercises and questions, and several opportunities to gather points to test and prove your preparation. You can add to the mark acquired at the exam by conducting projects aiming at improving aspects and/or materials of the course in a broad sense.
In preparing yourself for this exam,
take profit of the material (text and correction for each previous exam) available at the website of the course:

http://profs.sci.univr.it/~rrizzi/classes/RO/index.html

We also suggest to consult the three files:
prepararsi_esame.pdf, procedura_esame.pdf and dopo_esame.pdf
contained in folder 000-INFO-ESAME-000 contained, at the same page, among the folders of each previous exams. The approach and spirit with which you should elaborate your answers to the exercises is indeed related to some deep methodological messages at the core of the course, and it might turn difficult to achieve full satisfaction and recognizement at the exam without having adopted these approaches which can go easily overlooked.

There are 4 exam sessions each academic year (June, July, September, February). The exam is the very same regardless on whether you have attended or not the course. The archives of the past exams, the relative corrections, and the videos of the classes, all can help overcoming the difficulties of the non-attending student.

Type D and Type F activities

Modules not yet included

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, except for specific practical or lab activities, attendance is not mandatory. Regarding these activities, please see the web page of each module for information on the number of hours that must be attended on-site.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Graduation

Attachments

List of theses and work experience proposals

theses proposals Research area
Formule di rappresentazione per gradienti generalizzati Mathematics - Analysis
Formule di rappresentazione per gradienti generalizzati Mathematics - Mathematics
Mathematics Bachelor and Master thesis titles Various topics
Stage Research area
Internship proposals for students in mathematics Various topics

Gestione carriere


Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.