Ability to recognize and model network optimization problems as Integer Linear Programming problems.
Knowledge of fundamental algorithmic techniques for solving large scale Integer Linear Programming problems.
Knowledge of commercial and open source Integer Linear Programming solvers.
Content:
Formulations of Integer and Binary Programs: The Assignment Problem; The Stable Set Problem; Set Covering, Packing and Partitioning; Minimum Spanning Tree; Traveling Salesperson Problem (TSP); Formulations of logical conditions.
Optimality, Relaxation and Bounds. Geometry of R^n: Linear and aune spaces; Polyhedra: dimension, representations, valid inequalities, faces, vertices and facets; Alternative (extended) formulations; Good and Ideal formulations.
LP based branch-and-bound algorithm: Preprocessing, Branching strategies, Node and variable selection strategies, Primal heuristics.
Network Problems: formulations and algorithms. Constrained Spanning Tree Problems; Constrained Shortest Path Problem; Multicommodity Flows; Symmetric and Asymmetric Traveling Salesman Problem; Vehicle Routing Problem Steiner Tree Problem; Network Design. Local Search Tabu search and Simulated Annealing MIP based heuristics.
Heuristics for network problems: local search, tabu search, simulated annealing, MIP based heuristics.
A network of +20 European and non-European Universities, coordinated by Department of Information Engineering, Computer Science and Mathematics (DISIM) at University of L'Aquila in Italy (UAQ)