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Event

Introduction to Operations Research I [SS232550040]

Type
lecture (V)
Präsenz/Online gemischt
Term
SS 2023
SWS
2
Language
Deutsch
Appointments
14
Links
ILIAS

Lecturers

Organisation

  • Diskrete Optimierung und Logistik

Part of

Literature

  • Nickel, Rebennack, Stein, Waldmann: Operations Research, 3. Auflage, Springer, 2022
  • Hillier, Lieberman: Introduction to Operations Research, 8th edition. McGraw-Hill, 2005
  • Murty: Operations Research. Prentice-Hall, 1995
  • Neumann, Morlock: Operations Research, 2. Auflage. Hanser, 2006
  • Winston: Operations Research - Applications and Algorithms, 4th edition. PWS-Kent, 2004

Appointments

  • 18.04.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 25.04.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 02.05.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 09.05.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 16.05.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 23.05.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 06.06.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 13.06.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 20.06.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 27.06.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 04.07.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 11.07.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 18.07.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)
  • 25.07.2023 09:45 - 11:15 - Room: 50.35 Hörsaal am Fasanengarten (HS a.F.)

Note

Examples for typical OR problems.

Linear Programming: Basic notions, simplex method, duality, special versions of the simplex method (dual simplex method, three phase method), sensitivity analysis, parametric optimization, game theory.

Graphs and Networks: Basic notions of graph theory, shortest paths in networks, project scheduling, maximal and minimal cost flows in networks.

Learning objectives:

The student

  • names and describes basic notions of linear programming as well as graphs and networks,
  • knows the indispensable methods and models for quantitative analysis,
  • models and classifies optimization problems and chooses the appropriate solution methods to solve optimization problems independently,
  • validates, illustrates and interprets the obtained solutions.