Università degli Studi di Roma "Tor Vergata"

http://didattica.uniroma2.it/informazioni/index/insegnamento/172763-Modelli-Per-La-Gestione-Di-Sistemi-Complessi
Prerequisiti: There are no mandatory prerequisites to meet. It is necessary to know the foundations of graph theory and network optimization, and the basic methods of Operations Research including those of integer programming.
Obiettivi: Students acquire knowledge about the methodological, theoretical and application aspects of advanced topics of operations research. In particular, a set of modeling and algorithmic tools for problem solving for the management of complex systems in the production, transportation and logistics services with the aim of analyzing models, methods and the main applications. At the end of the course, the student will acquire the necessary skills to analyze and solve optimization problems in the areaa of machine scheduling, project scheduling and distribution problems (*knowledge and understanding skills*). In particular, the student will be able to learn the advanced tools for modeling and solving optimization problems within project scheduling by developing specific problem solving skills to solve typical decision-making problems in the industrial, business and general complex systems (*ability to apply knowledge and understanding*). The reference to application contexts and the need to identify important elements and their relationships in the study of an optimization model stimulate *judgment autonomy*, while the synthesis required in model definition through a suitable mathematical language stimulates *communicative abilities*. Lastly, the advanced topics of Operations Research learned in the course contributes to the development of *learning ability* by the student, putting him/her in a position to be able to deepen the topics discussed in an autonomous way.

http://didattica.uniroma2.it/informazioni/index/insegnamento/172763-Modelli-Per-La-Gestione-Di-Sistemi-Complessi
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Programma di Modulo 1:
Introduzione ai Sistemi Complessi: Contesto di riferimento; Il processo decisionale; Struttura concettuale di un DSS; La componente modellistica di un DSS. Machine Scheduling: Introduzione e definizioni generali; Classificazione e rappresentazione dei problemi di machine scheduling; Modelli di scheduling su macchina singola; Modelli di scheduling su macchine parallele; Modelli di scheduling di tipo flow-shop, open-shop e job-shop; Tecniche di risoluzione euristiche ed esatte per i modelli analizzati; Esempi e applicazioni. Project Management: Introduzione e aspetti chiave del project management; La pianificazione delle attivita' e il project scheduling. Project Scheduling: Tecniche reticolari; Problemi con risorse illimitate e vincoli di precedenza tradizionali: l'analisi dei tempi con il CPM, il PERT, l'analisi del trade-off tempi-costi con il CPM; Modelli e tecniche di risoluzione; Esempi e applicazioni.

http://didattica.uniroma2.it/informazioni/index/modulo/156202M4054-Modulo-1