Lecturer: Giancarlo Ferrari Trecate  

Course name: Automazione industriale
Course code: 064017
Degree course: Ingegneria Elettrica, Ingegneria Elettronica, Ingegneria Informatica, Ingegneria dei Servizi
Disciplinary field of science: ING-INF/04
L'insegnamento è caratterizzante per: Ingegneria Elettrica, Ingegneria Elettronica e delle Telecomunicazioni
The course relates to: Ingegneria Elettrica, Ingegneria Elettronica e delle Telecomunicazioni
University credits: CFU 5
Course website: http://sisdin.unipv.it/labsisdin/teaching/courses/ails/
files/ails.php

Specific course objectives

The main goal is to let students familiarize with basic techniques for process planning and management. In particular, methods and algorithms of management science for modelling and solving complex decision problems will be presented.

Course programme

Automation of production processes
Modeling of production processes. Flexible production processes. Management science. Operations research for decision problems.

Mathematical programming for decision problems
Modelling of decision problems: variables, cost and constraints. Basics of convex programming. Examples of decision problems including product mix, resource allocation, transport and portfolio selection problems.

Linear Programming (LP) problems
Geometry of LP. Fundamental theorem of LP. Algorithms for LP problems. The simplex method: phase 1 and 2. Tableau form of the simplex method. Sensitivity analysis.

Duality theory
Dual problems in mathematical programming: strong and weak-duality, constraints qualification for convex programming. Optimality and KKT conditions. Duality for LP and relations between primal and dual optimizers.

Optimization problems on graphs
Basics of computational complexity theory. Shortest spanning tree problem: Kruskal's algorithm. Shortest path problem: Dijkstra's and Floyd-Warshall algorithms. Flow networks: maximum flow problems and Ford-Fulkerson algorithm. Project planning: AOA models and the critical path method. PERT analysis. Dynamic programming: Bellman principle, cost-to-go and Bellman iterations. Application of dynamic programming to optimal control of finite state machines and to shortest path problems.

Course entry requirements

Basic knowledge on algorithms and control theory.

Course structure and teaching

Lectures (hours/year in lecture theatre): 30
Practical class (hours/year in lecture theatre): 18
Practicals / Workshops (hours/year in lecture theatre): 0
Project work (hours/year in lecture theatre): 0

Suggested reading materials

C. Vercellis. Modelli e Decisioni: Strumenti e Metodi per le Decisioni Aziendali. Esculapio, 1997.

M. Fischetti. Lezioni di ricerca operativa, 2 edizione. Edizioni Libreria Progetto, Padova, 1999.

English textbooks will be provided upon request..

Testing and exams

Closed-book, closed-note written exam.