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 in Matematica applicata - 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. 2014/2015
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3° Year activated in the A.Y. 2015/2016
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Uno o due insegnamenti tra i seguenti per un totale di 12 cfu| Modules | Credits | TAF | SSD |
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Uno o due insegnamenti tra i seguenti per un totale di 12 cfu| Modules | Credits | TAF | SSD |
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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.
Operations Research (2015/2016)
Teaching code
4S00001
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
MAT/09 - OPERATIONS RESEARCH
Period
II semestre dal Mar 1, 2016 al Jun 10, 2016.
Learning outcomes
This course aims to introduce the student to some basic models and to the main methodologies in the optimization field, with a particular attention to dynamic programming, combinatorial optimization, graphs, linear programming. Complexity theory is introduced and used as a tool advertising its methodological impact. The role of (integer) linear programming within the OR community is illustrated.
Program
Basic notions: models and algorithms, computational complexity, recursion and induction, invariants and monovariants, graphs, convex sets, polyhedra and cones.
Some of the models in Dynamic Programming: maximum increasing subsequence, maximum common subsequence, knapsack models.
Some of the models in graphs: Eulerian ed Hamiltonian paths and cycles, planar graphs and their duals, bipartite graphs, shortest paths, minimum spanning trees, max flow/min cut, maximum matching.
Linear programming: mathematical formulation of linear programming problems; equivalent forms, standard form; mathematical structure, geometry of linear programming, properties.
The simplex algorithm: vertices and basic solutions; optimality conditions; tableau method, auxiliary problem, two-phases method.
Duality theory: the fundamental duality theorem of linear programming, the dual simplex algorithm; economic interpretation; sensitivity analysis.
Integer linear programming: the cutting plane method; the branch and bound.
Network optimization: the minimum spanning tree problem, the shortest path problem, the maximum flow problem.
A more detailed program as intended, the day-by-day program of the last edition of the course, and the ongoing program of the current edition are available at the web-page of the course:
http://profs.sci.univr.it/~rrizzi/classes/RO/index.html
Examination Methods
Written final examination.
Past exams with answers can be found at the web-page of the course:
http://profs.sci.univr.it/~rrizzi/classes/RO/index.html
