Slides from Lectures and Tutorials

• Day 1: Introduction and Applications of Optimization
  • Introduction to Optimization
  • Applications of Optimization
  • Tutorial 1

• Day 2: Case Study and Methods for Unconstrained Optimization
  • Case Study: Design of Thermal Insulation System
  • Optimality and Methods for Unconstrained Optimization
  • Tutorial 2

• Day 3: Newton and Conjugate Gradient Methods
  • Newton and Quasi-Newton Methods
  • Conjugate Direction Methods
  • Tutorial 3 also download Zip archive with Matlab routines you can modify

• Day 4: Trust-Region Methods and Bound Constrained Optimization
  • Restricted Step Methods
  • Methods for Bound Constrained Optimization
  • Tutorial 4 new version of the Matlab routines Zip archive with Matlab routines you can modify

• Day 5: Optimality Conditions, Convexity, and Duality
  • Optimality Conditions
  • Convexity and Duality
  • Tutorial 5

• Day 6: Linear and Quadratic Programming
  • Linear Programming
  • Quadratic Programming
  • Tutorial 6
    • Data file for transshipment model network.dat
    • Data file for portfolio model portfolio.dat
    • Part of Student.mod model file part.mod

• Day 7: Nonlinear Programming Methods Part I
  • Sequential Quadratic Programming
  • Interior-Point and Augmented Lagrangian Methods
  • Tutorial 7
    • Data files for sparse optimization SparseOpt.dat, lasso6_20_2.dat, lasso20_100_14.dat

• Day 8: Nonlinear Programming Methods Part II
  • Globalization Strategies and Mechanisms
  • Active-Set Methods for Large-Scale NLP
  • Tutorial 8
    • Model and run files for 1D UFL optimization UFL.mod, UFL.ampl, and a data file for multi-dimensional UFL UFL1.dat (you need to write your own model file)