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040491 KU Implementation of Optimization Techniques (MA) (2018S)

8.00 ECTS (4.00 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.

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).

Details

max. 20 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Thursday 01.03. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 08.03. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 15.03. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 22.03. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 12.04. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 19.04. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 26.04. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 03.05. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 17.05. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 24.05. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 07.06. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 14.06. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday 18.06. 16:45 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 21.06. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Thursday 28.06. 15:00 - 18:15 PC-Seminarraum 1 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 2017 for Windows Desktop (including debugging and preprocessor directives)
* Basic concepts of the C++ programming language (data types and operators, selective structures, iteration structures, input and output with files, arrays, functions, structures, pointers, standard template library, recursive functions).
* 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)

Assessment and permitted materials

* [35%] Homework: Programming Exercises (28%) & Theory questions (7%)
* [30%] Mid-Term Exam
* [35%] End-Term Exam

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. At the beginning of each class groups will be randomly selected to present their code (resp. solution method).
The amount of work for the homework exercises increases throughout the semester, therefore the amount of points which can be gained is weighted according to their workload (i.e. exercises at the beginning of the semester are worth less points than exercises at the end of the semester).
Attempts of cheating by groups (e.g. uploading code which was not written by themselves) of single students (e.g. no contribution to the exercise) can be penalized by deducting up to twice as many points as the exercise is worth.

Theory questions have to be ticked on Moodle until Thursday 12:00 o'clock. At the beginning of each class students will be selected randomly to present the answers to the theory questions. Again, attempts of cheating can be penalized by deducting up to twice as many points as the question is worth.

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. Failure to do so (without prior notification of absence) will be considered as an attempt of cheating.

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.

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 two written exams has to be positive (>= 50%). The other grades are distributed as follows:
4: 50% to <63%
3: 63% to <75%
2: 75% to <87%
1: 87% to 100%

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, standard template library, recursive functions, etc.).
* Implementation of optimization methods for various problems that arise in production and logistics.

Reading list

All teaching material (slides, exercises, sample solutions, etc.) are available on the elearning 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: Mo 07.09.2020 15:29