Universität Wien

040147 UK Special Topics in Production/Logistics/SCM: Softwaretools in Decision Support (2022S)

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

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. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 02.03. 15:00 - 16:30 Digital
  • Wednesday 09.03. 15:00 - 16:30 Digital
  • Wednesday 16.03. 15:00 - 16:30 Digital
  • Wednesday 23.03. 15:00 - 16:30 Digital
  • Wednesday 30.03. 15:00 - 16:30 Digital
  • Wednesday 06.04. 15:00 - 16:30 Digital
  • Wednesday 27.04. 15:00 - 16:30 Digital
  • Wednesday 04.05. 15:00 - 16:30 Digital
  • 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 15.06. 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

This course gives an introduction to programming for decision support (DS) applications. The language of choice is Python, although the course will focus on fundamental programming concepts that also exist in other programming languages. The ultimate goal is to learn how to implement algorithms to solve optimization problems such as the Traveling Salesperson Problem (TSP).

The course covers the following topics:
* Understand what are DS systems and what is the role of programming in DS.
* Get familiar with Spyder, an integrated development environment for Python.
* Basic concepts of programming, such as variables, operators, conditional statements, loops, functions, and input and output from/to files.
* Implementation of construction and improvement heuristics for the TSP

Assessment and permitted materials

Homework 20% (4x5%)
Present and discuss your solution to the exercises, active participation in class (10%)
Tests 50% (2x25%)
Project work 20%

Minimum requirements and assessment criteria

Know what is a decision support system

Know why programming is useful for decision support

Understand the fundamentals of programming

- simple data structures, arithmetic and boolean operations, control flow (conditional statements and loops), functions, input/output

- no advanced data types, no recursion, no classes, no inheritance, no exception handling, no graphical user interfaces

Be able to write python programs to solve specified problems

- simple methods for the Traveling Salesman Problem (TSP)

0% - 49% : 5

50% - 62% : 4

63% - 74% : 3

75% - 86% : 2

87% - 100% : 1

Examination topics

Python fundamentals:
- Variables and operators
- Conditional statements and loops
- Functions
- Input/Output
Practice on the TSP:
- Construction heuristic
- Improvement heuristic

Reading list

The Python tutorial
Downey, Allen B.: Think Python. O'Reilly, 2014. Free book available

Association in the course directory

Last modified: Th 11.05.2023 11:27