KU Special Topics in Smart Production and SCM (Master)

The course special topics in production, logistics and supply chain management (SCM) focuses on a selection of new and interesting applications in logistics. The considered applications are in the field of humanitarian logistics, green logistics, logistics in health care. All the selected applications have in common that besides the classical cost-oriented objectives also client-centered or environmental-centered objectives are of importance. Therefore in these applications usually more than one objective is of relevance. From a theoretical point of view the course has a strong focus on the three important steps in solving a real-world decision problem: modelling, developing a solution technique and data analytics. In the modelling part mainly mixed integer programs will be developed – with a focus on multiple objectives. As solution techniques commercial solvers (excel), heuristics, column-generation based heuristics and set covering/set partitioning based heuristics are designed and used. In the generation of input data machine learning and deep learning concepts are deviced. At the end of the course the student should be able to model (basic) real-world problems, design mixed-integer programming based heuristics and understand the basics of machine and deep learning.

Course content

  • General Introduction (Overview)
  • Modelling (with a focus on multiple objectives):Long-haul Transportation, Transshipment, Vehicle Allocation, Driver Assignment, Hazardous Material Transportation)
  • Applications: humanitarian logistics, green logistics and pollution routing, electro-mobility, logistics in health care
  • Solution techniques – exact and heuristics: MIPit, epsilon-constraint, heuristics, column-generation, set-covering/partitioning heuristics
  • Data: Machine learning/Deep Learning

Language of Instruction



  • Gianpaolo Ghiani, Gilbert Laporte, Roberto Musmanno (2013), Introduction
  • to Logistics Systems Management, 2nd edition
  • Research articles