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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
TLE18S1
Degree Programme in International Logistics
Small groups
Group 1
Course
TEEN6550
No reservations found for realization TEEN6550-3001!

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

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