Università Roma Tre

Overview on decision making and Decision Support Systems (DSS). Model Driven DSS.
Mathematical modeling (examples of LP, ILP, and NLP formulations). Basics on computational complexity.
Introduction to Business Analytics. Predictive analytics, optimal classification trees, examples.
Prescriptive analytics. Heuristic algorithms: constructive heuristics, local search, variable depth local search, Tabu Search, Simulated Annealing, genetic algorithms, hints to other metaheuristics.
Robust Optimization.
Study of real world cases (optimization of the flows in the distribution of frozen food, optimization of staff shifts in hospital departments, optimial routing for the collection of material for laboratory analysis, optimal management of the warehouse of a company that deals with online sales, ....).

1. Modelli e metodi decisionali in condizioni di incertezza e rischio, di G. Ghiani, R. Musmanno (a cura di), McGraw-Hill Education, 2009.
2. Slides e notes given by the lecturer