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Event

Introduction to Operations Research II [WS192530043]

Type
lecture (V)
Term
WS 19/20
SWS
2
Language
Deutsch
Appointments
15
Links
ILIAS

Lecturers

Organisation

  • Kontinuierliche Optimierung

Part of

Literature

  • Nickel, Stein, Waldmann: Operations Research, 2. Auflage, Springer, 2014
  • 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

  • 17.10.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 24.10.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 31.10.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 07.11.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 14.11.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 21.11.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 28.11.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 05.12.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 12.12.2019 09:45 - 11:15 - Room: 10.11 Seminarraum Hauptgebäude
  • 19.12.2019 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 09.01.2020 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 16.01.2020 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 23.01.2020 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 30.01.2020 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal
  • 06.02.2020 09:45 - 11:15 - Room: 11.40 Johann-Gottfried-Tulla-Hörsaal

Note

Integer and Combinatorial Programming: Basic notions, cutting plane metehods, branch and bound methods, branch and cut methods, heuristics.

Nonlinear Programming: Basic notions, optimality conditions, solution methods for convex and nonconvex optimization problems.

Dynamic and stochastic models and methods: dynamical programming, Bellman method, lot sizing models, dyanical and stochastic inventory models, queuing theory.

Learning objectives:

The student

  • names and describes basic notions of integer and combinatorial optimization, nonlinear programming, and dynamic programming,
  • 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.