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Dati Insegnamento
Stampe
Manifesto
Dati Insegnamento
Contesto
Anno Accademico 2023/2024
Corso di Studi Dott. - MI (1380) Ingegneria dell'Informazione / Information Technology
Anno di Corso 1

Scheda Insegnamento
Codice Identificativo 061652
Denominazione Insegnamento ROBUST OPTIMIZATION
Tipo Insegnamento MONODISCIPLINARE
Crediti Formativi Universitari (CFU) 5.0
Programma sintetico Celebrating 20 years of renewed and flourishing interest in the robust optimization paradigm, this course will introduce students to the means of hedging risks in large managerial decision problems where distribution assumptions cannot be made. More specifically, the students will become acquainted with the main tools that are used in the application of the robust optimization paradigm: convex theory (duality theory, saddle point theorem, Karush-Kuhn-Tucker conditions), data-driven uncertainty sets design, adjustable decision manipulation, tractable reformulation and decomposition algorithms for problems of infinite size. In addition, the course will cover a set of practical applications where the use of such tools is called-for. Applications will be inspired from a diversified range of fields of practice such as logistics, finance, marketing, etc. At the end of the course, the students should be able to: - identify a business management or engineering situation presenting a robust optimization problem, - represent this problem under a suitable mathematical model, - exploit available historical observations to adequately characterize the uncertainty - identify robust solutions using cutting edge software and algorithms
Settori Scientifico Disciplinari (SSD) --

Dettaglio
Scaglione Nome Programma dettagliato
Da (compreso) A (escluso)
A ZZZZ Jabali Ola, Delage Erick Hans
manifestidott v. 1.10.0 / 1.10.0
Area Servizi ICT
22/06/2024