Universität Wien

040147 UK Special Topics in Produktion/Logistik/SCM: Softwaretools im Decision Support (2022S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
DIGITAL
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Mittwoch 02.03. 15:00 - 16:30 Digital
  • Mittwoch 09.03. 15:00 - 16:30 Digital
  • Mittwoch 16.03. 15:00 - 16:30 Digital
  • Mittwoch 23.03. 15:00 - 16:30 Digital
  • Mittwoch 30.03. 15:00 - 16:30 Digital
  • Mittwoch 06.04. 15:00 - 16:30 Digital
  • Mittwoch 27.04. 15:00 - 16:30 Digital
  • Mittwoch 04.05. 15:00 - 16:30 Digital
  • Mittwoch 11.05. 15:00 - 16:30 Digital
  • Mittwoch 18.05. 15:00 - 16:30 Digital
  • Mittwoch 25.05. 15:00 - 16:30 Digital
  • Mittwoch 01.06. 15:00 - 16:30 Digital
  • Mittwoch 08.06. 15:00 - 16:30 Digital
  • Mittwoch 15.06. 15:00 - 16:30 Digital
  • Mittwoch 22.06. 15:00 - 16:30 Digital
  • Mittwoch 29.06. 15:00 - 16:30 Digital

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

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

Art der Leistungskontrolle und erlaubte Hilfsmittel

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

Mindestanforderungen und Beurteilungsmaßstab

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

Prüfungsstoff

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

Literatur

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

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Do 11.05.2023 11:27