Optimization and Simulation (5 cr)
Code: TEEN6550-3001
General information
- Enrollment
-
03.08.2020 - 30.08.2020
Registration for the implementation has ended.
- Timing
-
07.09.2020 - 19.12.2020
Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 4 cr
- Virtual portion
- 1 cr
- Mode of delivery
- Blended learning
- Unit
- School of Technology
- Campus
- Main Campus
- Teaching languages
- English
- Seats
- 0 - 30
- Degree programmes
- Bachelor's Degree Programme in International Logistics
- Teachers
- Pasi Lehtola
- Scheduling groups
- Ryhmä 1 (Capacity: 30 . Open UAS : 0.)
- Groups
-
TLE18S1Degree Programme in International Logistics
- Small groups
- Group 1
- Course
- TEEN6550
Evaluation scale
0-5
Objective
The students know the concepts and methods of optimization and simulation. They are able to formulate a working-life problem as an optimization task or a simulation study and solve the problem using a computer.
EUR-ACE Knowledge and Understanding: Students must know and understand the mathematical principles, concepts and methods underlying logistics.
EUR-ACE Engineering Analysis: Students must have the ability to identify, formulate and solve engineering problems using mathematical methods.
TELNA: Students are able to use mathematics in a technical environment.
Content
Linear and non-linear optimization, elements of graph theory, optimization in networks, simulation studies, elements of queuing theory, input and output data analysis. The use of Excel, Mathcad and other computer programs for optimization and simulation.
Materials
Will be described in the learning environment following the course description.
Teaching methods
Contact lessons and exercises
Self study
Learning tasks
Exam schedules
The date and execution of the exam will be announced in the beginning of the course.
Completion alternatives
The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.
Student workload
Contact lessons 36 hours
Independent study 36 hours
Learning tasks 36 hours
Preparing for exam 12 hours
Assessment criteria, satisfactory (1)
Sufficient (1): Student has gained knowledge of course objectives but face challenges to utilize them in practice.
Satisfactory (2): Student has gained knowledge of course objectives and can utilize them partly in practice.
Assessment criteria, good (3)
Good (3): Student has gained understanding of course objectives and can utilize them in practice.
Very good (4): Student has attained very good level of course objectives and can apply them into practice.
Assessment criteria, excellent (5)
Excellent (5): Student has attained an excellent level of course objectives and can apply them into practice in innovative manner.
Qualifications
The students know probability distributions and can work with computer programs Excel and Mathcad
Further information
Open AMK: at most 5 students if there are seats in the classroom