This is an archived course. A more recent version may be available at ocw.mit.edu.

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    This course is divided into 5 segments, as described below.

    lec # TOPICS
    Linear Optimization
    1 Introduction
    2 The Geometry of LO
    3 The Simplex Method
    4 The Simplex Method II
    5 Duality Theory I
    6 Duality Theory II
    7 Sensitivity Analysis
    8 Robust Optimization
    9 Large Scale Optimization
    Network Flows
    10 Network Optimization - Introduction and Applications
    11 Network Optimization - The Network Simplex Algorithm
    Discrete Optimization
    12 Discrete Optimization
    13 Exact Methods for IP
    14 Lagrangean Methods
    15 Heuristic Methods
    Dynamic Optimization
    16 Dynamic Programming
    Nonlinear Optimization
    17 Applications of Nonlinear Optimization
    18 Optimality Conditions and Gradient Methods for Unconstrained Optimization
    19 Line Searches and Newton's Method
    20 The Conjugate Gradient Algorithm Optimality Conditions for Constrained Optimization
    21 The Affine Scaling Algorithm
    22 Barrier Interior Point Algorithms
    23 Semidefinite Optimization
    24 Semidefinite Optimization (cont.)