Servizi per la didattica
PORTALE DELLA DIDATTICA

Optimization methods for engineering problems

01RGBRV

A.A. 2019/20

Course Language

Inglese

Course degree

Doctorate Research in Ingegneria Elettrica, Elettronica E Delle Comunicazioni - Torino

Course structure
Teaching Hours
Lezioni 30
Teachers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Repetto Maurizio Professore Ordinario ING-IND/31 30 0 0 0 4
Teaching assistant
Espandi

Context
SSD CFU Activities Area context
*** N/A ***    
2019/20
PERIOD: MAY The course aims at introducing the main operative concepts of nonlinear optimization both on deterministic (search methods, gradient methods, quadratic optimization) and on stochastic (genetic algorithm, swarm, artificial immune etc.) basis. Some application examples in the field of electromagnetics and energy application will be presented.
PERIOD: MAY The course aims at introducing the main operative concepts of nonlinear optimization both on deterministic (search methods, gradient methods, quadratic optimization) and on stochastic (genetic algorithm, swarm, artificial immune etc.) basis. Some application examples in the field of electromagnetics and energy application will be presented.
1. Introduction to applied optimization in engineering 2. Nonlinear deterministic optimization for single value problems 3. Stochastic optimization for single value problems 4. Multi-objective optimization 5. Application examples
1. Introduction to applied optimization in engineering 2. Nonlinear deterministic optimization for single value problems 3. Stochastic optimization for single value problems 4. Multi-objective optimization 5. Application examples
Subject Start Date Start Time End Time Description Location Prof. Scalar Optimization Wed 27 May 9.00 12.00 lesson Virtual ClassroomRepetto Scalar Optimization Wed 27 May 14.30 17.30 lesson Virtual ClassroomRepetto Scalar Optimization Thu 28 May 9.00 12.00 lesson Virtual ClassroomRepetto Scalar Optimization Fri 29 May 9.00 12.00 lab Virtual ClassroomRepetto Vector Optimization Wed 3 Jun 9.00 12.00 lesson Virtual ClassroomFreschi Vector Optimization Wed 3 Jun 14.30 17.30 lab Virtual ClassroomFreschi Vector Optimization Thu 4 Jun 9.00 12.00 lesson Virtual ClassroomFreschi Vector Optimization Fri 5 June 9.00 12.00 lab Virtual ClassroomFreschi Final Test Mon 8 Jun 9.00 12.00 lab Virtual ClassroomFreschi & Repetto
Subject Start Date Start Time End Time Description Location Prof. Scalar Optimization Wed 27 May 9.00 12.00 lesson Virtual ClassroomRepetto Scalar Optimization Wed 27 May 14.30 17.30 lesson Virtual ClassroomRepetto Scalar Optimization Thu 28 May 9.00 12.00 lesson Virtual ClassroomRepetto Scalar Optimization Fri 29 May 9.00 12.00 lab Virtual ClassroomRepetto Vector Optimization Wed 3 Jun 9.00 12.00 lesson Virtual ClassroomFreschi Vector Optimization Wed 3 Jun 14.30 17.30 lab Virtual ClassroomFreschi Vector Optimization Thu 4 Jun 9.00 12.00 lesson Virtual ClassroomFreschi Vector Optimization Fri 5 June 9.00 12.00 lab Virtual ClassroomFreschi Final Test Mon 8 Jun 9.00 12.00 lab Virtual ClassroomFreschi & Repetto
ModalitÓ di esame:
Exam:
Gli studenti e le studentesse con disabilitÓ o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'UnitÓ Special Needs, al fine di permettere al/la docente la declinazione pi¨ idonea in riferimento alla specifica tipologia di esame.
Exam:
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
Esporta Word


© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti