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Special Topics in Smart Production and SCM (Master)

Language of Instruction:


Course Description:

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.


  • 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


For the Excel based homeworks an introductory tutorial is offered at the beginning of the semester. The participation is voluntary. Seats in the lab will be assigned according to a first come, first serve principle due to capacity bottlenecks.

Dates for the tutorial: TBA

Content of the tutorial: general introduction in Excel and Excel Solver, preparation for the homework (modelling and the usage of excel solver)


20% homework presented and discussed in class (including a short seminar presentation), 40% midterm exam, 40% final exam.


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






      @ University of Vienna

      Production and Operations Management with International Focus
      Faculty of Business, Economics and Statistics
      University of Vienna
      Oskar-Morgenstern-Platz 1
      A-1090 Vienna
      T: +43-1-4277-379 52
      F: +43-1-4277-837952
      University of Vienna | Universitätsring 1 | 1010 Vienna | T +43-1-4277-0