Content
The advanced seminar in logistics and supply chain management focuses on recent research
progress on varying topics, e.g. supply chain performance measurement, metamodelling and
metaheuristics (see below for example).
- Metamodelling identifies strategic cost relationships between logistics performance measures
and aggregate problem parameters. Thereby, empirical research methods (such as regression
models) are combined with mathematical optimization and simulation models (such as mixed-
integer programming or discrete event simulation) to identify best practice relationships. Several
topics with applications in transportation, inventory management and procurement are available.
- Supply chain design under uncertainty often involves combinatorial optimization problems. The
combination of scenario-based modelling and the combinatorial nature of the problem suggest the
application of modern heuristic optimization concepts. Several topics on different applications and
search methods are available.
Learning outcomes
The objective of the module is to equip the participants with the necessary skill and tools for a
successful master thesis project.
Specifically, the aim is to be able to:
- Read and understand recent research contributions
- Pursue interesting research questions
- Conduct a literature study and/or numerical study and/or implementation
- Structure and organize research methods and results
- Write a seminar paper
- Present research findings and defend them in a discussion
Examination
The examination consists of a written seminar paper including implemented optimization or
simulation models (75%), an oral presentation (20%) and a discussion (5%). The seminar paper
to be submitted one week prior to the presentation should cover 15-20 pages and is to be written
in the style of current publications of peer-reviewed journal articles, including an introduction, a
literature review, a description of the model and algorithms, numerical results and conclusions to
show the competencies to clearly describe a research problems, the ability to conduct a literature
view, to structure the material and demonstrate technical writing, design an experiment and
describe and visualize the results, and show the ability to critically discuss the results. At the end
of the module, students present their work in a 30 minutes presentation to the chair members
and other seminar participants to show the ability to design and deliver a research presentation
using different available media and visualization tools and defend the results in a critical group
discussion. In the discussion part, every student has to read and summarize the paper and
presentation of one other participant to demonstrate the ability to summarize and moderate a
research discussion with all other seminar participants.
Prerequisites
One module in the field of Operations & Supply Chain Management and the MOS course.
Teaching & learning methods
In an introductory session, the current theme of the module is explained by the lecturer and the
various available seminar topics are elaborated in detail. Also information on relevant literature
for the problem settings is introduced, wich forms the basis of the students' seminar papers. After
the introductory session, students will work out the topic on their own, by using their abbilities of
conducting literature research, mathematical modelling, programming and analyses. Throughout
the whole time, they receive guidance from a supervisor of the chair. Different milestones are to be
achieved at specific dates, such as a preliminary outline of the seminar paper, first research results
and the final paper. Following the submission of the final paper, presentations and discussions of
all students' seminar papers are conducted, usually spanning one or several days, where amongst
others also presentation, moderation and discussion skills are trained.
Media & reading list
Presentation, Various forms of literature (Journal Articles, Books, Report, Conference Proceedings,
etc.)
'Dependent on seminar focus, e.g.:
'- Kleijnen, J.P.C. (2008), Design and Analysis of Simulation Experiments, Springer
- Bianchi, L. Dorigo, M., Gambardella, L.M., Gutjahr, W. (2009), A survey on stochastic
combinatorial optimization, NatComput 8:239-287
- Gutjahr, W. (2011), Recent trends in stochastic combinatorial optimization, Central European
Journal of Computer Science 1(1): 58-66.
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