C6.2 Continuous Optimisation (2022-23)

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  General

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    Announcements Forum
  • Select activity Discussion Forum

    

    Discussion Forum
• Select section Course Materials

  Course Materials

  • Select activity Lectures 1 and 2

    Introduction. Optimality conditions for unconstrained problems. (2021 Videos 1-3; Sheet 1)

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    • Lectures 1 and 2
      • C62_Lecture1a.pdf
      • C62_Lecture1b.pdf
      • C62_Lecture2.pdf
  • Select activity Lectures 3 and 4

    Methods for unconstrained optimization. Linesearch algorithms (2021 Videos 4-6; Sheet 2)

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    • Lectures 3 and 4
      • C62_Lecture3a.pdf
      • C62_Lecture3b.pdf
      • C62_Lecture4.pdf
  • Select activity Lecture 5

    Steepest descent methods (2021 Video 7, Sheet 2)

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    • Lecture 5
      • C62_Lecture5.pdf
  • Select activity Lecture 6

    Newton's method for unconstrained optimization (2021 Videos 8-9; Sheet 2)

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    • Lecture 6
      • C62_Lecture6a.pdf
      • C62_Lecture6b.pdf
  • Select activity Lecture 7

    Quasi-Newton methods. Nonlinear least-squares and Gauss-Newton methods. (2021 Videos 10-11; Sheet 3)

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    • Lecture 7
      • C62_lecture7.pdf
  • Select activity Lectures 8 and 9

    Trust region methods. (2021 Videos 12-14, Sheet 3)

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    • Lectures 8 and 9
      • C62_Lecture8.pdf
      • C62_Lecture9a.pdf
      • C62_Lecture9b.pdf
  • Select activity Lectures 10 and 11

    Optimality conditions for constrained problems. (2021 Videos 15-16, Sheet 4)

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    • Lectures 10 and 11
      • C62_Lecture10and11.pdf
  • Select activity Lecture 12

    Penalty methods for constrained optimization (2021 Videos 17, Sheet 4)

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    • Lecture 12
      • C62_Lecture12.pdf
  • Select activity Lecture 13

    Augmented Lagrangian methods (2021 Videos 18, Sheet 4)

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    • Lecture 13
      • C62_Lecture13.pdf
  • Select activity Lectures 14 and 15

    Interior point methods for inequality constrained optimization problems (2021 Videos 19-20, Sheet 4)

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    • Lectures 14 and 15
      • C62_Lecture14and15.pdf
  • Select activity Lecture 16

    SQP methods for constrained optimization (2021 Video 21) The content here is nonexaminable. 

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    • Lecture 16
      • C62_Lecture16.pdf
  • Select activity Additional lecture material - nonexaminable

    Complete proof of trust region methods convergence. Proof of second-order optimality conditions for constrained problems.

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    • Additional lecture material - nonexaminable
      • Lecture9_CompleteProof_Trust_Region.pdf
      • Lecture11_ProofTheorem19.pdf
  • Select activity Additional Resources

    Mathematical Background. Resources and bibliography

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    • Additional Resources
      • C62_MathematicalBackground.pdf
      • C62_Resources.pdf
      • Taylor.pdf
  • Select activity Optimization Booklet

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    • Optimization Booklet
      • Gould_Continuous_Optimization_Algorithms.pdf
      • Hauser_Cont_Opt_lecturenotes.pdf
  • Select activity Sheet 1

    

    Sheet 1 Assignment
  • Select activity Sheet 2

    

    Sheet 2 Assignment
  • Select activity Sheet 3

    

    Sheet 3 Assignment
  • Select activity Sheet 4

    

    Sheet 4 Assignment
  • Select activity Numerical Laboratories

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    • Numerical Laboratories
      • C62_Numerical_labs.pdf
      • Newton method.m
      • Rosenbrock function.m
      • Scaled quadratic function.m
      • Steepest descent method.m