Logistics Systems Modelling and Optimisation

5 credits

Syllabus, Master's level, 1TE776

A revised version of the syllabus is available.
Code
1TE776
Education cycle
Second cycle
Main field(s) of study and in-depth level
Industrial Engineering and Management A1N, Technology A1N
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 6 March 2018
Responsible department
Department of Civil and Industrial Engineering

Entry requirements

120 credits. 20 credits in mathematics. Industrial Management

Learning outcomes

After a successfully completed course the student should be able to:

  • account for statistics and probability theory used for modeling logistics and production systems as well as for analysis of inputs and results,
  • account for the principles of event-driven simulation,
  • account for the general theoretical and methodological framework for simulation projects including experimental design,
  • • account for various optimization techniques and their specific applications in optimizing logistics and production systems,
  • apply conceptual models for analysis of different system scenarios,
  • optimize logistics and production systems using a specific conceptual simulation-based optimization tool.

Content

Mathematical modelling of logistic systems including queue models. Event-driven simulation and analysis of different types of logistics and production systems, such as functional workshop, production line, party and drag control and aggregated supply chains. System optimization where the effective front of target conflicts is analysed using metaheuristic algorithms.

Instruction

Lectures, laboratory sessions.

Assessment

Laboratory sessions, written assignments, written exam.

No reading list found.

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