- Docente: Enrico Malaguti
- Credits: 6
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: First cycle degree programme (L) in Engineering Management (cod. 0925)
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from Sep 18, 2024 to Dec 18, 2024
Learning outcomes
Introduction to logic and mathematical models of optimization and
decision problems by using mathematical programming and numerical
simulation. Capability of analyzing the complexity of problems and
ability to solve and interpret some optimization problems.
Course contents
Requirements/Prior knowledgeStudents are required to have basic knowledge on set theory, vectorial and matricial calculus, and statistics. In addition, knowledge and understanding about coding and programming is a necessary pre-requisite.
For this reason, students are strongly suggested to attend this course only after passing these exams:
- Analisi matematica e geometria e algebra T-AB
- Analisi matematica T-B
- Fondamenti di Informatica T-1
Course Contents
- Introduction: Decision and Optimization problems. Models of Decision and Optimization problems and their classification. Methodology of Operations Research. Exact and Heuristic Algorithms. Brief introduction to computational complexity of problems and algorithms.
- Linear Optimization. examples of models. Simplex algorithm in graphic forms. Introduction to the use of a solver package.
- Integer Linear Optimization. Formulations of an integer linear optimization problems. Graphical solution. Branch and bound method basic principles.
- Numerical Simulation: process interaction models and event programming models.
Readings/Bibliography
Recommended
slides and lecture notes available online
Useful references
S. MARTELLO, D. VIGO, ESERCIZI DI RICERCA OPERATIVA, PROGETTO LEONARDO, BOLOGNA, 1999.
S. MARTELLO, D. VIGO, ESERCIZI DI SIMULAZIONE NUMERICA, PROGETTO LEONARDO, BOLOGNA, 1999.
S. MARTELLO, LEZIONI DI RICERCA OPERATIVA, PROGETTO LEONARDO, BOLOGNA, 2002
M. FISCHETTI, LEZIONI DI RICERCA OPERATIVA, EDIZIONI LIBRERIA PROGETTO, PADOVA, 1995
Teaching methods
The course consists of lectures and class exercises.
The lectures discuss the theoretical and algorithmic aspects of the various arguments.For each argument some case studies will be presented and analyzed.Assessment methods
The final exam is designed to assess the achievement of learning objectives:
- provide basic tools for modelling and solving optimization problems;
- apply simulation models for complex models with queues.
The exam includes two parts that determine the final score.
The exam is only written.
Students may use book and notes.
Teaching tools
Teaching material used during the course and some lecture notes will be available to the students on AMS campus.
Links to further information
https://www.unibo.it/sitoweb/enrico.malaguti/news/44faf217
Office hours
See the website of Enrico Malaguti
SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.