Course: Mathematical Methods in Transport Control

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Course title Mathematical Methods in Transport Control
Course code KTRD/SDMMR
Organizational form of instruction no contact
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 0
Language of instruction Czech, English
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
Course content
- Deterministic models. - Stochastic models. - Basics of simulation modelling. Generation of stochastic input values in simulation models. - Decision making problems. Methods of game theory, application for decision making in conflicting situations. - Schedules. Transport application, spatial, time and circulation schedules. - Basic principles of periodic transport systems, mathematical methods, systematic transport processes. - Integrated periodic timeschedule - properties, dependencies modelled by graph theory, optimization, patterns and conditions. - Integrated interchange junctions - characteristics, parameters, layout optimization, mathematical dependencies.

Learning activities and teaching methods
Work with text (with textbook, with book)
  • Preparation for an exam - 30 hours per semester
  • Preparation for an exam - 30 hours per semester
  • Independent critical reading - 30 hours per semester
  • Independent critical reading - 30 hours per semester
Learning outcomes
The subject about mathematical methods in transport for the state doctoral exam.
Overview about mathematical methods in transport.
Prerequisites
To have knowledge of the subject KTRD/PMMVR.

Assessment methods and criteria
Oral examination

Positive evaluation of the answer to the given question at the state doctoral exam proving that the student understands the issue. It is evaluated by an examiner as well as state exam committee.
Recommended literature
  • Achimská, V. Modelovanie systémov. Žilina, 2011. ISBN 978-80-554-0450-9.
  • Albright, S. Christian. Data analysis & decision making. Mason: Thomson South-Western, 2006. ISBN 0-324-40086-1.
  • Asmussen, Soren. Stochastic simulation : algorithms and analysis. New York: Springer Science+Business Media, 2007. ISBN 978-0-387-30679-7.
  • Drdla, Pavel. Osobní doprava regionálního a nadregionálního významu. Pardubice: Univerzita Pardubice, Dopravní fakulta Jana Pernera, 2018. ISBN 978-80-7560-189-6.
  • Eiselt, Horst A.. Decision analysis, location models, and scheduling problems. Berlin: Springer-Verlag, 2010. ISBN 978-3-642-07315-1.
  • Kušnierová, J., Hollarek, T. Metódy modelovania a prognózovania prepravného a dopravného procesu. Žilina, 2000. ISBN 80-7100-673-4.
  • Liebchen. Periodic Timetable Optimization in Public Transport. Berlin, 2006. ISBN 978-3-86624-150-X.
  • Nelson, Barry L. Stochastic modeling : analysis and simulation. New York: McGraw-Hill, 1995. ISBN 0-07-046213-5.
  • Ortúzar Salas, Juan de Dios. Modelling transport. Chichester: John Wiley & Sons, 2011. ISBN 978-0-470-76039-0.
  • Pinedo, Michael L. Scheduling : theory, algorithms, and systems. New York: Springer, 2012. ISBN 978-1-4614-1986-0.
  • Schneeweiss, Christoph. Distributed decision making. Berlin: Springer-Verlag, 2003. ISBN 3-540-40201-2.
  • Univerzita Pardubice. Modelování technologických procesů v dopravě. Pardubice: Univerzita Pardubice Dopravní fakulta Jana Pernera, 2011. ISBN 978-80-7395-442-0.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester