Network Design 2018-2019


Network Design (Progetto di Reti) is a 12 CFU integrated course made of two modules: Network Flows (formerly Progetto e Ottimizzazione di Reti) and Network Optimization (formerly Ottimizzazione Combinatoria 2)

Schedule

Network Flows

  • TbD

Network Optimization

  • TbD

Office Hours

Tue 11:00-13:00, Thu 11:00 - 13:00

Course Contents

Module Network Flows

  • Network Flows Problem: introduction and definitions
  • Maximum Flows and the path packing problem. Flows and cuts: Max-Flow/Min-Cut theorem. Augmenting path algorithms: Ford and Fulkerson algorithm, Edmonds and Karp algorithm. Generic Preflow-Push algorithm. Flows with lower bounds.
  • Maximum Flows: additional topics and applications. Flows in Unit Capacity Networks. Flows in Bipartite Networks. Network Connectivity.
  • Minimum Cuts. Global Minimum Cuts. Node Identification Algorithm. Random Contraction. Applications.
  • Minimum-Cost Flow Problems. Definition and applications. Optimality Conditions. The Ford-Bellman algorithm for the shortest path problem. Primal algorithms: Augmenting Circuit Algorithm for the Min Cost Flow Problem.
  • Network Simplex Algorithms. Applications of Min Cost Flows.

Module Network Optimization

  • 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.
  • Mixed Integer Formulations: Modeling Fixed Costs; Uncapacitated Facility Location; Uncapacitated Lot Sizing; Discrete Alternatives; Disjunctive Formulations.
  • Optimality, Relaxation and Bounds. Geometry of R^n: Linear and affine 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.
  • Cutting Planes algorithms. Valid inequalities. Automatic Reformulation: Gomory's Fractional Cutting Plane Algorithm. Strong valid inequalities: Cover inequalities, lifted cover inequalities; Clique inequalities; Subtour inequalities. Branch-and-cut algorithm.
  • Software tools for Mixed Integer Programming.
  • Lagrangian Duality: Lagrangian relaxation; Lagrangian 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.
  • Heuristics for network problems: local search, tabu search, simulated annealing, MIP based heuristics.

Textbooks

Reference books

  • L.A. Wolsey, Integer Programming, Wiley, 1998.
  • Cook, Cunningham, Pulleyblank, Schrijver , Combinatorial Optimization, Wiley,1998.
  • Ahuja, Magnanti, Orlin, Network Flows, Prentice Hall, 1993.

Further readings

Slides and Notebooks

Slides are in Italian. English slides and Network Optimization slides are available on request Notebooks

Software