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.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026The 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 enrollment year.
1° Year
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2° Year activated in the A.Y. 2010/2011
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Tre insegnamenti a scelta tra i seguenti
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Tre insegnamenti a scelta tra i seguenti
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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.
Algorithms - ALGORITMI AVANZATI (2009/2010)
Teaching code
4S02709
Teacher
Credits
4
Also offered in courses:
- Advanced algorithms of the course Masters in Computer Science
- Advanced algorithms of the course Masters in Intelligent and Multimedia Systems
Language
Italian
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
1st Semester dal Oct 1, 2009 al Jan 31, 2010.
Learning outcomes
The goal of this course is to introduce some advanced paradigms for algorithms development and analysis in order to determine good approximate solutions for hard optimization problems.
Program
Main concepts recall about computational problems: definition, instances, encoding, precise and approximate models. Optimization computational problem.
Main concepts recall about algorithms: computational resources, input encoding, input size/cost, computational time. Worst and average analysis. Computational time and growth order.
Computational time vs. hardware improvements: main relations. Efficient algorithms and tractable problems.
Divide et impera paradigm
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Definition and application to some problems.
Greedy paradigm
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Definition and application to some problems. Matroids and greedy algorithms.
Backtracking technique
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Definition and application to some problems.
Branch & Bound technique
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Definition and application to some problems.
Dynamic programming paradigm
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Definition and application to some problems.
Memoization and Dynamic programming.
Local search tecnique
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Definition and application to some problems.
Approximations algorithms
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Definition and some application examples.
Simulated annealing.
Tabù search.
Probabilistic algorithms
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Definition and few application examples.
Numerical probabilistic algorithms, Monte Carlo algorithms and Las Vegas algorithms. Examples: Buffon's needle, Pattern Matching and Universal hashing.
Author | Title | Publishing house | Year | ISBN | Notes |
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Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani | Algorithms (Edizione 1) | McGraw-Hill Higher Education | 2007 | 978-0-07-352340-8 | Testo secondario |
Alan Bertossi | Algoritmi e strutture dati (Edizione 1) | UTET | 2000 | 88-7750-611-3 | Testo secondario |
T. Cormen, C. Leiserson, R. Rivest, C. Stein | Introduzione agli Algoritmi e Strutture Dati (Edizione 2) | McGraw-Hill | 2005 | 88-386-6251-7 | Testo consigliato per la prima parte del corso |
Steven S. Skiena | The Algorithm Design Manual (Edizione 2) | Springer | 2008 | 9781848000698 | Testo secondario per il corso ma ottimo come manuale di riferimento per un'ampia classe di problemi. |
Examination Methods
The examination consists of a written test (at the same time as the other two module tests) that lasts 1 hour (all tests together last 3 hours). The grade in this module is worth 1/3 of the grade in the Algorithms examination.