Mathematical Optimization at Work

General information




Other material for this course is available at the associated Git repository. The drawings made during the video lectures are collected in this document.

Week Topics and Slides Material
14 Introduction. Pyomo (slides). Intro to Python; Pyomo; Sheet 1
  Pyomo (examples). Model Fitting (linear and non linear models). Sheet 2; Solution S.2
  Installations. Preprocessing. [ABGRW]
16 MILP Formulations for Traveling Salesman Problem Sheet 3; [P] or [DFJ] or [MTZ] or [A] or [ABCC] or [OAL]
  Cutting Planes for TSP  
  More on TSP. Network Flows duality Solution S.3
17 Cut-and-Solve [CZ]; Sheet 4; Solution S.4
  Modeling tricks [KN1,KN2,ABGRW]
18 Timetabling [dW]; [LL]
  Timetabling Assignment 1
19 Lagrangian Relaxation for MILP [AMO ch 16]; [Fi]
  Exercises Sheet 5; [IB]; [Fi2]; [JB]
  Implementation, LR for TSP Solution S.5; [Wo ch 10]
20 Vehicle Scheduling [BCG]; [CG]
  Exercises Sheet 6
  Dantzig Wolfe decomposition [AMO ch 17]; [Wo ch 11]; [LD]
21 Vehicle Routing: Compact models; Set Partitioning formulation and CG [Fe]
  Vehicle Routing: Cutting and Branching [Fe]
  Exercises on Column Generation Sheet 7
22 Crew Scheduling; RCSP [SGSK]; [GM]; Assignment 2; Solution Asg 2
  Benders Decomposition [DJ, sec 3.5]; Video