28639 - Operations Research T-A (L-Z)

Course Unit Page

SDGs

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

Quality education Industry, innovation and infrastructure Sustainable cities Responsible consumption and production

Academic Year 2021/2022

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 also using the personal computer.

Course contents

Requirements/Prior knowledge
Students 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
Fluent spoken and written Italian is a necessary pre-requisite. All lectures and tutorials will be in Italian. Some study material will be in English.

 

Course Contents

    1. 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.
    2. Linear Optimization. examples of models. Simplex algorithm in graphic forms. Introduction to the use of a solver package.
    3. Integer Linear Optimization. Formulations of an integer linear optimization problems. Graphical solution. Branch and bound method basic principles.
    4. Numerical Simulation: process interaction models and event programming models.

    Readings/Bibliography

    Recommended

    slides 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. 

    Students must register for the exam on Almaesami.

    Teaching tools

    All teaching material used during the course will be available to the students on InsegnamentiOnLine.

    Links to further information

    https://www.unibo.it/sitoweb/michele.monaci/avvisi/1b3facd2

    Office hours

    See the website of Michele Monaci