Models and Algorithms for Optimization

1) Scheduling problems in production and healthcare contexts; 2) distribution logistics problems with real constraints (node and arc routing); 3) financial problems (portfolio selection, risk measures); 4) metaheuristic algorithms; 5) mathematical programming based methods; 6) general-purpose algorithms (Kernel Search); 7) Exact algorithms for combinatorial problems; 8) Location problems; 9) Network design and optimization; 10) Synchromodality; 11) multi-objective problems; 12) Combinatorial optimization problems; 13) Optimization problems in static, dynamic, and stochastic contexts;14) Routing problems in healthcare; 15) worst-case analysis in combinatorial optimization problems;