Optimization and Simulation (5 cr)
Code: TEEN6550-3002
General information
Enrollment
02.08.2021 - 05.09.2021
Timing
30.08.2021 - 17.12.2021
Number of ECTS credits allocated
5 op
Virtual portion
2 op
Mode of delivery
60 % Face-to-face, 40 % Online 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
Teacher in charge
Pasi Lehtola
Groups
-
TLP21VSBachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
-
TLE19S1Degree Programme in International Logistics
Objectives
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.
Learning materials and recommended literature
Taylor, B. W. (2018) Introduction to Management Science. Pearson
Banks, Carson, Nelson & Nicol (2014). Discrete-Event System Simulation. Pearson.
Teaching methods
The contact lessons are in a computer class and involve use of computers. The theory is acquired before class exercises independently. The learning is reached by assignments where theory is put into practice.
Exam dates and retake possibilities
The date and execution of the exam will be announced in the beginning of the course.
Alternative completion methods
The admission procedures are described in the degree rule and the study guide.
Student workload
Contact lessons about 30 hours
Independent study about 40 hours
Learning tasks about 50 hours
Preparing for exam about 10 hours
Further information for students
The assessment is based on learning tasks and exams.
An equivalent course in Finnish TLXM4580 Optimointi ja simulointi.
Open AMK: at most 5 students if there are seats in the classroom
Exchange students:
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
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.
Evaluation criteria, good (3-4)
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.
Evaluation criteria, excellent (5)
Excellent (5): Student has attained an excellent level of course objectives and can apply them into practice in innovative manner.
Prerequisites
The students know probability distributions and can work with computer programs Excel and Mathcad