040161 KU Implementation of Optimization Techniques - Part 2 (MA) (2022S)
Continuous assessment of course work
Labels
REMOTE
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 07.02.2022 09:00 to Mo 21.02.2022 23:59
- Registration is open from Th 24.02.2022 09:00 to Sa 14.05.2022 23:59
- Deregistration possible until Sa 21.05.2022 23:59
Details
max. 35 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
11.05.
15:00 - 16:30
Digital
Wednesday
18.05.
15:00 - 16:30
Digital
Wednesday
25.05.
15:00 - 16:30
Digital
Wednesday
01.06.
15:00 - 16:30
Digital
Wednesday
08.06.
15:00 - 16:30
Digital
Wednesday
22.06.
15:00 - 16:30
Digital
Wednesday
29.06.
15:00 - 16:30
Digital
Information
Aims, contents and method of the course
Assessment and permitted materials
* [100%] Homework/Projects: Programming Exercises & Theory questions
Attempts of cheating might be penalized by deducting up to twice as many points as the exercise is worth. In severe cases, cheating (copying code) may even lead to failing the course and an entry of “X” in the record of exams.
The amount of work for the programming exercises increases throughout the course. The achievable points for the exercises are therefore weighted according to their workload (i.e. exercises at the beginning of the course are worth less points than exercises at the end of the course).
Attempts of cheating might be penalized by deducting up to twice as many points as the exercise is worth. In severe cases, cheating (copying code) may even lead to failing the course and an entry of “X” in the record of exams.
The amount of work for the programming exercises increases throughout the course. The achievable points for the exercises are therefore weighted according to their workload (i.e. exercises at the beginning of the course are worth less points than exercises at the end of the course).
Minimum requirements and assessment criteria
In order to obtain a positive grade on the course, at least 50% of the overall points have to be achieved, and at least 50% of the projects have to be positive. The other grades are distributed as follows:
1: >87% to 100%
2: >75% to <87.5%
3: >63% to <75%
4: >50% to <62.5%
1: >87% to 100%
2: >75% to <87.5%
3: >63% to <75%
4: >50% to <62.5%
Examination topics
* Basic and advanced concepts of the C# programming language (data types and operators, methods, classes, loops, input and output with files, arrays).
* Implementation of optimization methods for various problems that arise in production and logistics.
* Implementation of optimization methods for various problems that arise in production and logistics.
Reading list
The teaching material (slides, exercises, sample solutions, etc.) is available on the e-learning platform Moodle.
In order to access this material you need a valid UNET account. Moodle weblogin: https://moodle.univie.ac.at/Useful links:
https://docs.microsoft.com/en-us/dotnet/csharp/tutorials/intro-to-csharp/
https://dotnet.microsoft.com/learn/csharp
https://www.tutorialspoint.com/csharp/index.htm
https://www.tutorialsteacher.com/csharp/csharp-tutorials
In order to access this material you need a valid UNET account. Moodle weblogin: https://moodle.univie.ac.at/Useful links:
https://docs.microsoft.com/en-us/dotnet/csharp/tutorials/intro-to-csharp/
https://dotnet.microsoft.com/learn/csharp
https://www.tutorialspoint.com/csharp/index.htm
https://www.tutorialsteacher.com/csharp/csharp-tutorials
Association in the course directory
Last modified: Th 11.05.2023 11:27
The course covers following topics:
* Get familiar with Microsoft Visual Studio
* Basic and advanced concepts of the C# programming language (data types and operators, methods, classes, loops, input and output with files, arrays)
* Methodological knowledge for developing algorithms and their translation into C# (a step by step approach to select suitable data and program structures)
* Implementation of Constructive Methods and Improvement Methods for the Traveling Salesperson Problem (TSP) and the Vehicle Routing Problem (VRP)