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Advanced Operations Research

Curriculum

  • 1 Section
  • 39 Lessons
  • 10 Weeks
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  • Advanced Operations Research
    39
    • 2.1
      Lecture 1 – Introduction & Linear Programming
    • 2.2
      Lecture 2 – Revised Simplex Algorithm
    • 2.3
      Lecture 3 – Simplex Method for Bounded Variables
    • 2.4
      Lecture 4 – One Dimensional Cutting Stock Problem Part 1
    • 2.5
      Lecture 5 – One Dimensional Cutting Stock Problem Part 2
    • 2.6
      Lecture 6 – Dantzig-Wolfe Decomposition Algorithm
    • 2.7
      Lecture 7 – Dantzig-Wolfe Decomposition Algorithm Primal- Dual Algorithm
    • 2.8
      Lecture 8 – Primal-Dual Algorithm
    • 2.9
      Lecture 9 – Goal Programming- Formulations
    • 2.10
      Lecture 10 – Goal Programming Solutions Complexity of Simplex Algorithm
    • 2.11
      Lecture 11 – Complexity of Simplex Algorithm: Integer Programming
    • 2.12
      Lecture 12 – Integer Programming-Formulations
    • 2.13
      Lecture 13 – Solving Zero-One Problems Part 1
    • 2.14
      Lecture 14 – Solving Zero-One Problems Part 2
    • 2.15
      Lecture 15 – Branch & Bond Algorithm for Integer Programming
    • 2.16
      Lecture 16 – Cutting Plane Algorithm
    • 2.17
      Lecture 17 – All Integer Primal Algorithm
    • 2.18
      Lecture 18 – All Integer Dual Algorithm
    • 2.19
      Lecture 19 – Network Models
    • 2.20
      Lecture 20 – Shortest Path Problem
    • 2.21
      Lecture 21 – Successive Shortest Path Problem
    • 2.22
      Lecture 22 – Maximum Flow Problem
    • 2.23
      Lecture 23 – Minimum Cost Flow Problem
    • 2.24
      Lecture 24 – Traveling Salesman Problem (TSP)
    • 2.25
      Lecture 25 – Branch and Bound Algorithms for TSP
    • 2.26
      Lecture 26 – Heuristics for TSP Part 1
    • 2.27
      Lecture 27 – Heuristics for TSP Part 2
    • 2.28
      Lecture 28 – Chinese Postman Problem
    • 2.29
      Lecture 29 – Vehicle Routeing Problem
    • 2.30
      Lecture 30 – Queueing Models
    • 2.31
      Lecture 31 – Single Server Queueing Models
    • 2.32
      Lecture 32 – Multiple Server Queueing Models
    • 2.33
      Lecture 33 – Game Theory
    • 2.34
      Lecture 34 – Critical Path Method
    • 2.35
      Lecture 35 – Quadratic Programming
    • 2.36
      Lecture 36 – Integer Programming
    • 2.37
      Lecture 37 – All Integer Dual Algorithm
    • 2.38
      Lecture 38 – Mixed Integer Linear Programming
    • 2.39
      Lecture 39 – Benders Partitioning Algorithm
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Lecture 4 – One Dimensional Cutting Stock Problem Part 1
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Lecture 6 – Dantzig-Wolfe Decomposition Algorithm
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