Aktuelle Ansätze in der Produktion und Logistik [M.WIWI-BWL.0028]

Topic: Simulations for logistics in the service sector
M.Sc. Beatriz Beyer, Prof. Dr. Matthias Klumpp

1. Background and Learning Objectives
Simulation models and simulation software are increasingly being used in companies in production, logistics and supply chain management to support decision-making (Mejia et al. 2016; Knol et al. 2019; Goienetxea Uriarte et al. 2017; Boero et al. 2015; Gottwalt et al. 2011; Jahangirian et al. 2010; Biethahn et al. 1999; Robinson 2004; Zhang et al. 2011). The seminar looks at various topics in the field of decision support using different simulation models. The aim is the independent, research-oriented and reflected scientific treatment of topics of simulation as decision support tool for logistics in the service sector. The students learn the basics of three simulation methods and apply these methods for specific cases of the service sector in three short papers. The aim is the independent, research-oriented and reflected scientific treatment of topics of simulation as decision support in logistics and supply chain management. The seminar is part of the DAAD project IVAC.

      At the end of the seminar the students should be able to:
    • Understand and explain the concept of simulations and the differences between discrete-event simulations, system dynamics and agent based simulations.
    • Apply three different simulation methods to specific cases for the logistics of the
      service sector.
    • Understand and use simulation software tools.
    • Understand and discuss the results of simulation models as a decision support tool.

2. Schedule and target group
The seminar is targeted at Master students of the Faculty of Business and Economics and at students from the University of Trento. The seminar will be in English and takes place online. Four compulsory block seminars are being held as follow:

      Wednesday, April 14th 2021, from 1 to 5pm:
    • Opening session, lecture on simulations and on discrete-event simulation. Start of the first group assignment.
    • Wednesday, May 19th 2021, from 1 to 5pm:
    • Presentation of first assignment on discrete event siumlation, lecture on system dynamics (SD). Start of the 2nd group assignment.
    • Wednesday, June 16th 2021, from 1 to 5pm:
    • Presentation of second assignment on system dynamics, lecture on agent-based modeling (ABM). Start of the 3rd group assignment.
    • Wednesday, July 7th 2021, from 1 to 5pm
    • Presentation of third assignment on agent-based modeling. Feedback and final conclusions.

3. Deadlines for the short papers:

  • 1st paper (Discrete-Event): May 19th 10 am
  • 2nd paper (SD): June 16th 10 am
  • 3rd paper (ABM): July 7th 10 am

  • 4. Registration and organisation
    Registration is compulsory and required until the 22.03.2021 via Stud.IP. The registration is only complete if you attend the introductory session on the 14.04.2021. Withdrawal is only possible until Wednesday, 21.04.2021. From there on, all course efforts are graded. Students will work togehter in groups of 2-3 students on three short paper assignments (2,500 to 3,000 words) and three short presentations (15 minutes each team) regarding discrete-event simulations, system dynamics and agent based simulations. Teams will be randomly allocated for each team task. Events are fully digital. In each lecture one simulation method is introduced as input for the group assignments. The group assignments start after each lecture and are due until the next scheduled lecture. Students from the Engineering Department of Trento University will join the seminar. The total number of participants in this seminar is limited to 12 students. [1]

    5. Literature
    • Biethahn, Jörg; Hummeltenberg, Wilhelm; Schmidt, Bernd; Stähly, Paul; Witte, Thomas (Hg.) (1999): Simulation als betriebliche Entscheidungshilfe. State of the Art und neuere Entwicklungen. Heidelberg: Physica-Verlag HD.
    • Boero, Riccardo; Morini, Matteo; Sonnessa, Michele; Terna, Pietro (2015): Agent-based models of the economy. From theories to applications: Palgrave Macmillan. Online verfügbar unter http://www.worldcat.org/oclc/903473861
    • Goienetxea Uriarte, Ainhoa; Ruiz Zúñiga, Enrique; Urenda Moris, Matías; Ng, Amos H.C. (2017): How can decision makers be supported in the improvement of an emergency department? A simulation, optimization and data mining approach. In: Operations Research for Health Care 15, S. 102–122. DOI: 10.1016/j.orhc.2017.10.003.
    • Gottwalt, Sebastian; Ketter, Wolfgang; Block, Carsten; Collins, John; Weinhardt, Christof (2011): Demand side management—A simulation of household behavior under variable prices. In: Energy Policy 39 (12), S. 8163–8174. DOI: 10.1016/j.enpol.2011.10.016.
    • Jahangirian, Mohsen; Eldabi, Tillal; Naseer, Aisha; Stergioulas, Lampros K.; Young, Terry (2010): Simulation in manufacturing and business. A review. In: European Journal of Operational Research 203 (1), S. 1–13. DOI: 10.1016/j.ejor.2009.06.004.
    • Knol, Arthur; Sharpanskykh, Alexei; Janssen, Stef (2019): Analyzing airport security checkpoint performance using cognitive agent models. In: Journal of Air Transport Management 75, S. 39-50.
    • Mejia, Jezreel; Muñoz, Mirna; Rocha, Álvaro; Calvo-Manzano, Jose (Hg.) (2016): Trends and Applications in Software Engineering. Proceedings of the 4th International Conference on Software Process Improvement CIMPS'2015. International Conference on Software Process Improvement. 1st ed. 2016. Cham: Springer (Advances in Intelligent Systems and Computing, 405). Online verfügbar unter http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1083975.
    • Robinson, Stewart (2004): Simulation modelling. The practice of model development & use. Chichester: Wiley.
    • Zhang, Ting; Gensler, Sonja; Garcia, Rosanna (2011): A study of the diffusion of alternative fuel vehicles. An agent-based modeling approach. In: Journal of Product Innovation Management 28, S. 152-168.