Università degli Studi di Napoli "Parthenope"

  1. Teaching
  2. MARITIME ECONOMY
  3. TECNICHE DI SIMULAZIONE

Stampa

TECNICHE DI SIMULAZIONE

Teaching schedule

Academic year: 
2018/2019
Belonging course: 
Course of Master's Degree Programme on MARITIME ECONOMY
Disciplinary sector: 
MATHEMATICAL METHODS OF ECONOMY, FINANCE AND ACTUARIAL SCIENCES (SECS-S/06)
Language: 
Italian
Credits: 
9
Year of study: 
1
Teachers: 
DE ANGELIS Pasquale Luigi
Cycle: 
Second semester
Hours of front activity: 
72

Language

Italian

Course description

Objectives of the course:
The aim of the course is to provide students with a base of knowledge of mathematical methods for optimization, with applications to transport problem and optimal resource allocation analysis;
2) advanced knowledge for planning and management of databases.

Expected learning outcomes
Knowledge and understanding: the student should be able to understand the mathematical methods used in linear optimization problems. It should also be able to use the normally available software (as a minimum, the resolver in Excel).
Applying knowledge and understanding: the student should be able to apply the acquired knowledge in solving real business planning problems such as maximizing profits or minimizing costs. To this end the teacher will discuss and illustrate some different real cases during the lessons; for non-attending students, assistance time will be provided.
Making judgements: the student should be able to use the acquired knowledge also in an autonomous way, by also applying them even in contexts not directly proposed.
Communication: the student should be able to answer in a clear and thorough way to the problem proposed in the written examination and the questions formulated inf the possible oral examination.
Lifelong learning skills: the student should be able to show a good learning ability, by widening, for example, his/her knowledge with use of relevant bibliographic references, The student should also be able to analyze and evaluate the impact and the constraints related complex situations.

Prerequisites

Linear algebra: systems of linear equations, vector and matrix calculus. Functions of several variables.
BASIC KNOWLEDGE OF DATA PROCESSING.
this is basically covered by the first-level courses offered by the university Parthenope in the economic area. For students coming from different first-level degree programs, an integration including a relevant bibliographic reference will be provided.

Syllabus

Unconstrained and constrained optimization problems. Introduction to Linear Programming.Transport problem Excel risolutorCase study.
Course organization
During the lessons the issues mentioned in the study program will be discussed and presented, together with applications and examples such as specific cases of regulation in typical markets or sectors. Additional didactic and support material is made available on the teacher web page, where slides presentation used at lesson can be found, together with additional material for deepening a number of thematic issues.

Teaching Methods

Textbooks

The main readings will be suggested at the beginning of the course. For students who speak Italian, the main reference is represented by the following book:
DE CESARE, MADDALENA, Introduzione alla Programmazione Lineare, Giappichelli

Learning assessment

The assessment is based on a structured written test aimed at evaluating the actual achievement of the objectives on part the students. In order to evaluate the depth in understanding general theoretical knowledge, a real problem is proposed. The students should be able to fully solve it by developing the mathematical formulation of the same and implementing the resolution software. The time allocated for completion of the test is 1 hour. The test runs on the computer and is evaluated in a scale from 0 to 30.

An oral examination can also be held, in case the teacher judges it useful to better ascertain the student’s knowledge. The vote of the oral examination is expressed in scale from 0 to 30, and it is averaged with the vote of written examination (equal weighting) in order to determine the final vote.

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