OVERVIEW

The course illustrates different methodologies for the optimization and optimal control of complex systems, with specific reference to problems of interest for management engineering.

AIMS AND CONTENT

LEARNING OUTCOMES

To formalize an optimization problem for planning and managing complex systems; to identify the most suitable optimization methods; to implement the optimization algorithms with specific software; to discuss the results and make sensitivity analyses on the solutions

AIMS AND LEARNING OUTCOMES

At the end of the course, the student will be able:
- to formalize a multi-objective optimization problem for complex systems, with specific reference to manufacturing and logistics systems, project management;
- to formalize an optimal control problem for complex systems, with specific reference to manufacturing and logistics systems, project management;
- to identify the most suitable optimization and control method for a specific application;
- to design and implement the optimization and control algorithms with specific software;
- to discuss the results and make sensitivity analyses on the solutions.

Besides these learning outcomes, the student who actively participates to lessons and team working activities can acquire the following  soft skills:
- social skills – basic level: capacity to manage social interactions, collaborative behaviour, constructive communication in different environments;
- capacity of learning to learn – basic level: awareness of the preferred learning stretegies, organization and evaluation of personal learning.

PREREQUISITES

There are no specific requirements.

TEACHING METHODS

The lessons consist in lectures given by the professor and team working activities with specific software. The team working activities are conceived to allow the students to learn how to formalize optimization and control problems and to implement them with specific software, and to develop critical analysis capabilities about the results obtained for applications in the management engineering field. The team working activities start in the classroom, under the supervision of the professor, after which each team is required to work independently and deliver a report of the project carried out, within a deadline to be agreed.

The team working activities allow the students who actively participate to acquire social skills (basic level) and the capacity of learning to learn (basic level).

Students who have valid certifications for Specific Learning Disorders (DSA), for disabilities or other educational needs are invited to contact the professor and the contact person for disabilities of the Polytechnic School, Prof. Federico Scarpa (federico.scarpa@unige.it), at the beginning of the course to agree on any teaching methods that, in compliance with the objectives of the course, take into account their individual learning approach.

SYLLABUS/CONTENT

Introduction to optimization
Multi-objective optimization methods
Multi-criteria analysis
Introduction to control
Optimal control
LQ problem
Model Predictive Control

RECOMMENDED READING/BIBLIOGRAPHY

The students can find all the slides used during the lectures and other teaching material on Aulaweb. In general, the notes taken during the lectures and the material available on Aulaweb are sufficient for adequately preparing for the exam. 

For an in-depth analysis of the subjects, students can consult the following texts:
- B.S. Blanchard, W.J. Fabrycky, Systems Engineering and Analysis, Prentice Hall International Series in Industrial & Systems Engineering, 2010
- R.T. Clemen, T. Reilly, Making Hard Decisions with Decision Tools, South-Western Cengage Learning, 2013
- P.P. Parlos, Multi-criteria decision making methods: a comparative study, Kluwer, 2000
- P. Bolzern, R. Scattolini, N. Schiavoni, Fondamenti di controlli automatici, McGraw-Hill
- D.P. Bertsekas, Dynamic Programming and Optimal Control, Athena Scientific, 2000
- J.M. Maciejowski, Predictive Control with Constraints, Prenctice Hall, 2002

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

https://corsi.unige.it/en/corsi/8734/studenti-orario

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam is oral. In the first part of the exam the student presents a project previously assigned by the professor. In the second part of the exam the student must answer to some open-ended questions on the contents of the course.

For students who have valid certifications for Specific Learning Disorders (DSA), for disabilities or other educational needs the professor identifies the specific modalities and supports for the exam, that will be determined on a case-by-case basis in agreement with the contact person for disabilities of the Polytechnic School.

Foreign students are allowed to take the exam in English.

ASSESSMENT METHODS

The exam aims to verify the following aspects about the knowledge of the student:
- knowledge regarding optimization and control methods for complex systems;
- ability to design optimization and control algorithms for specific numerical examples and real systems;
- ability to analyse the impact of the obtained solution on the systems and to make sensitivity analyses

The evaluation of the exam will consider not only the knowledge of the contents addressed in the course but also the reasoning and critical analysis skills of the student, as well as his/her capability to use a technical lexicon appropriate for the context.

FURTHER INFORMATION

Ask the professor for further information.