First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
Course unit
SCP4063217, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
SS1736, Degree course structure A.Y. 2014/15, A.Y. 2018/19
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination STOCHASTIC OPTIMIZATION
Website of the academic structure
Department of reference Department of Statistical Sciences
E-Learning website
Mandatory attendance No
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge LUIGI DE GIOVANNI MAT/09
Other lecturers CARLA DE FRANCESCO MAT/09

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines MAT/09 Operational Research 9.0

Course unit organization
Period Second semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Laboratory 1.5 14 23.5 No turn
Lecture 7.5 50 137.5 No turn

Start of activities 25/02/2019
End of activities 14/06/2019
Show course schedule 2019/20 Reg.2014 course timetable

Examination board
Board From To Members of the board
6 Commissione a.a.2019/20 01/10/2019 30/09/2020 DE GIOVANNI LUIGI (Presidente)
DE FRANCESCO CARLA (Membro Effettivo)
FISCHER MARKUS (Membro Effettivo)
5 Commissione a.a.2018/19 01/10/2018 30/09/2019 DE GIOVANNI LUIGI (Presidente)
DE FRANCESCO CARLA (Membro Effettivo)
FISCHER MARKUS (Membro Effettivo)

Prerequisites: Elementary Probability Theory.
Target skills and knowledge: The objective of the course is to provide a range of tools that may help in finding the best decisions when the information available is not deterministic and complete but is only known with some degree of stochasticity.
Examination methods: The grading will be based on a written test (plus a possible oral examination) and the presentation of a small project to be agreed with the Instructor.
The exam may be taken in italian or English
Course unit contents: The course program includes the following topics:
- Queuing Theory
- Decision Analysis
- Robust Optimization
- Markovian Decision processes
- Stochastic Optimization
- Revenue Management
- Discrete Event Simulation
- Simulation of Dynamic Systems
- Use of Simulation Packages
Planned learning activities and teaching methods: Lectures in the classroom and practical experimentation in the computer laboratory.
Additional notes about suggested reading: Besides the textbook (in Italian), further material will be made available in the web page dedicated to the course.
Textbooks (and optional supplementary readings)
  • G. Ghiani e R. Musmanno, Modelli e metodi decisionali in condizioni di incertezza e rischio. Milano: McGraw Hill, 2009. ISBN 978-88-386-6636-0 Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem based learning
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)