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040491 KU Implementation of Optimization Techniques - Part 1 (MA) (2018W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

The course KU Implementation of Optimisation Techniques (8 ECTS) as mentioned in the master’s curriculum Business Administration will not be offered any more in its original form. It is now split into two parts: Implementation of Optimization Techniques Part 1 (4 ECTS) and Implementation of Optimization Techniques Part 2 (4 ECTS). Hence, both courses are compulsory for students of Business Administration doing their Major in Smart Production and Supply Chain Management (as an equivalent to the old 8 ECTS course).

For students of International Business Administration and students of Business Administration who are NOT doing their Major in Smart Production and Supply Chain Management, this course can be chosen as elective course.

In general, there is no prior knowledge necessary to attend this course. However, it is suggested to complete the Introductory Phase of the Curriculum prior to visiting this course. Furthermore, having a basic knowledge of a programming language and/or algorithmic thinking is an advantage. For students who want to prepare for this course we recommend the following courses and resources:
* UK Special Topics in Production/Logistics/SCM: Softwaretools in Decision Support
* https://www.learncpp.com/
* https://www.cprogramming.com/tutorial/c++-tutorial.html

The course is particularly recommended to students, who want to write their thesis in the field Smart Production and Supply Chain Management

If students do not complete Part 1 successfully, those will be de-registered by the system for Part 2.

Details

max. 35 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

In case a lesson has to be canceled (e.g., due to illness), it will be rescheduled to the 29th of November. In this case the follow-up course Implementation of Optimization Techniques – Part 2 will start with a delay of one week on December, 6th.

Thursday 04.10. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 11.10. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 16.10. 08:00 - 09:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 18.10. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 23.10. 08:00 - 09:30 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 25.10. 15:00 - 18:15 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 30.10. 08:00 - 09:30 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 06.11. 08:00 - 09:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 08.11. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 13.11. 08:00 - 09:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 15.11. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Tuesday 20.11. 08:00 - 09:30 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 22.11. 15:00 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 22.11. 18:30 - 20:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 03.12. 08:00 - 09:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 03.12. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 10.12. 08:00 - 09:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 10.12. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 07.01. 08:00 - 09:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 07.01. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 14.01. 08:00 - 09:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 14.01. 09:45 - 11:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Aims, contents and method of the course

Overall objective: to learn "hands-on" how to implement optimization algorithms in C++.

The course covers following topics:
* Get familiar with Microsoft Visual Studio Community 2017 for Windows Desktop
* Basic concepts of the C++ programming language (data types and operators, selective structures, iteration structures, input and output with files, arrays, functions, structures, pointers, vectors)
* Methodological knowledge for developing algorithms and their translation into C++ (a step by step approach to select suitable data and program structures)
* Simple to slightly advanced programs, including the Nearest Neighbor Algorithm for the TSP

Assessment and permitted materials

* [30%] Homework: Programming Exercises (25%) & Theory questions (5%)
* [30%] Mid-Term Exam (pen and paper, closed book)
* [40%] End-Term Exam (programming, closed book)

The homework programming exercises can (and should be done) in groups of 2 - 3 people. They have to be uploaded in Moodle until latest Tuesday 23:59 o'clock prior to the next class. Theory questions are individual assessments and have to be ticked on Moodle until Thursday 12:00 o'clock. At the beginning of each class students/groups will be randomly selected to present their answer/code. In general, if a theory question is ticked or a programming exercise is uploaded students must be present in class, so that they can be chosen to present their homework.

Absence without a valid excuse can be penalized by deducting up to twice as many points as the ticked questions/exercises are worth. If one is asked to present the solution of a programming exercise but fails to do so, all points for programming exercises of the respective class will be canceled. Similarly, if one fails to answer a theory question, all ticks for theory questions of the respective class will be canceled.

Attempts of cheating by groups (e.g., uploading code which was partly not written by themselves) or single students (e.g., no contribution to the exercise) 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 one out of 2 written exams has to be positive (>= 50%). The other grades are distributed as follows:
1: 87% to 100%
2: 75% to <87%
3: 63% to <75%
4: 50% to <63%

Examination topics

* Basic concepts of the C++ programming language (data types and operators, selective structures, iteration structures, input and output with files, arrays, functions, structures, pointers, vectors, etc.)
* Implementation of programs that make use of the mentioned concepts of C++

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:
http://www.cplusplus.com/doc/tutorial/
http://www.cppreference.com

Association in the course directory

Last modified: We 13.03.2019 11:07