. – Operations Research
PROFESSOR LORENZO SCHIAVINA
Text under revision. Not yet approved by academic staff.
COURSE AIMS
To provide an overview of the most common operations research techniques and,
at the same time, teach students to produce models of these techniques on the
computer for experimental and - possibly - application purposes.
COURSE CONTENT
Prerequisites: The course illustrates how to write programs on the computer to
check the results of the models studied and look into their possible concrete
application.
For this purpose, the course includes a short introduction to Smalltalk language,
which is considered the most suitable for developing operations research
applications. It is also a useful tool for accessing existing already developed
models.
Ability to use the computer and knowledge of local and network tools are also
considered essential, along with familiarity with individual productivity tools.
Specific operations research topics:
• The operations research cycle: methods and development of applications.
• Mathematical programming: deterministic models for developing problem
optimization applications; in particular, in-depth study of the simplex algorithm for
primal and dual problems; sensitivity analysis; overview of zero-sum two-player
game theory; using existing tools to solve the problem.
• Deterministic and probabilistic mathematical models: overview of the statistical
concepts of probability, random variables and the tools needed to understand
probabilistic models; overview and brief introduction to queuing theory.
• Control of complex projects: introduction to the PERT method and use of
existing control packages.
• Simulation models: Monte Carlo method and random number generation for
developing application models.
• Introduction to stock management theory: economic order quantity model and
use of simulation for the most realistic solution to the problem; introduction to the
just-in-time production optimization approach.
• Creating and using expert systems: concept and application of expert systems
and introduction to the backpropagation algorithm; introduction to fuzzy logic for
creating expert systems; using the DIRO (data in - rules out) approach to develop
expert systems; use of the FuzzyWorld package with examples of applications of
various kinds.
READING LIST
Basic textbook:
L. SCHIAVINA, Metodi e strumenti per la modellizzazione aziendale. Come gestire il problem
solving e il decision making, Franco Angeli, Milan, 2006.
Textbooks and programs will also be recommended according to the topics dealt with.
TEACHING METHOD
All students are required to have a basic understanding of the use of Smalltalk on the
PC; the course is based on lectures and exercises on some of the topics covered, and
students may link up with the lecturer for clarification or doubts.
ASSESSMENT METHOD
Course participants have to set up working groups to develop their own applications on
proposed topics; however, students are assessed individually on how they illustrate and
present their work; the work carried out and relevant documentation has to be made
available on a specific freely-consultable website.
NOTES
Further information can be found on the lecturer's webpage
http://www2.unicatt.it/unicattolica/docenti/index.html or on the Faculty notice board.
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