Scheda programma d'esame
LOGISTICS
MARIA GRAZIA SCUTELLA'
Anno accademico2019/20
CdSDATA SCIENCE AND BUSINESS INFORMATICS
Codice255AA
CFU6
PeriodoPrimo semestre
LinguaItaliano

ModuliSettoreTipoOreDocente/i
LOGISTICSMAT/09LEZIONI48
MARIA GRAZIA SCUTELLA' unimap
Learning outcomes
Knowledge

The student who successfully completes the course will have a solid background about the main modeling techniques and some basic algorithmic approaches for managing logistic systems, both at design and at operational level. Specifically, he/she will be able to formulate, in a mathematical way, relevant location and transportation problems. In addition, he/she will be aware of basic approaches related to project management and inventory problems. Furthermore, the student will be able to implement, solve and analyze simple logistics problems by means of spreadsheet solvers.

Assessment criteria of knowledge

The student knowledge on models and methods in Logistics will be assessed during the oral examination. Furthermore, the student ability in modeling and analyzing simple logistics problems will be verified by means of a project and the associated written report.

 

Skills

At the end of the course the student will be able to formulate, in a mathematical way, relevant optimization problems, such as the ones arising in Logistics. Furthermore, he/she will be able to implement, solve and analyze simple logistics problems by means of spreadsheet solvers.

Assessment criteria of skills

Modeling and solving skills will be assessed via the project and during the oral examination.

Behaviors

The student will achieve competence in managing decision problems arising in Logistics and in developing mathematical based decision support systems.

Assessment criteria of behaviors

Via exercizes and discussion with the students.

Prerequisites

Basic notions of calculus and linear algebra.

Teaching methods

Delivery: face to face

Learning activities:

  • attending lectures
  • preparation of written report
  • participation to discussions
  • individual study
  • work in group 

Attendance: Advised

Teaching methods:

  • lectures
  • project work
Syllabus

After an introduction to Linear programming (LP), Integer Linear Programming (ILP) and Network Flow Problems, the main location problems (i.e. basic facility location models, maximum distance models, total or average distance models and location problems in the public sector) and the main transportation problems (i.e. Vehicle Routing Problems) will be presented and formulated via ILP. PERT and CPM methods to project management and basic inventory policies will be then discussed. Several examples will be presented, together with the solution of simple logistics problems by means of spreadsheet solvers.

Further details can be found at http://didawiki.cli.di.unipi.it/doku.php/magistraleinformaticaeconomia/log/start

Bibliography

Teacher lecture notes and files of examples are available at:

http://didawiki.cli.di.unipi.it/doku.php/magistraleinformaticaeconomia/log/start

Reference textbooks:

G. Ghiani, R. Musmanno. Modelli e Metodi per l'Organizzazione dei Sistemi Logistici, Pitagora, 2000

G. Ghiani, G. Laporte, R. Musmanno. Introduction to Logistics Systems Planning and Control, Wiley, 2004

C.T. Ragsdale. Spreadsheet Modeling & Decision Analysis, Fourth Edition, A Practical Introduction to Management Science, Thomson South-Western, 2004

Z. Drezner, H.W. Hamacher. Facility Location, Applications and Theory, Springer, 2002

P. Toth, D. Vigo. The Vehicle Routing Problem, SIAM, Monographs on Discrete Mathematics and Applications, 2002

 

Assessment methods

Methods:

  • Written report
  • Final oral exam

The written report, related to a project work that can be solved individually or in group, will contribute with a bonus (maximum +2) to the grade of the oral exam.

Ultimo aggiornamento 08/09/2019 14:42