C6.2 Continuous Optimisation (2024-25)
Section outline
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Introduction. Optimality conditions for unconstrained problems. (2021 Videos 1-3; Sheet 1)
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Methods for unconstrained optimization. Linesearch algorithms (2021 Videos 4-6; Sheet 2)
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Steepest descent methods (2021 Video 7, Sheet 2)
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Newton's method for unconstrained optimization (2021 Videos 8-9; Sheet 2)
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Quasi-Newton methods. Nonlinear least-squares and Gauss-Newton methods. (2021 Videos 10-11; Sheet 3)
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Trust region methods. (2021 Videos 12-14, Sheet 3)
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Optimality conditions for constrained problems. (2021 Videos 15-16, Sheet 4)
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Penalty methods for constrained optimization (2021 Videos 17, Sheet 4)
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Augmented Lagrangian methods (2021 Videos 18, Sheet 4)
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Interior point methods for inequality constrained optimization problems (2021 Videos 19-20, Sheet 4)
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SQP methods for constrained optimization (2021 Video 21) The content here is nonexaminable.
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Complete proof of trust region methods convergence. Proof of second-order optimality conditions for constrained problems.
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Mathematical Background. Resources and bibliography
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Opens: Friday, 17 January 2025, 11:20 PM
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Opens: Friday, 17 January 2025, 11:23 PM
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Opens: Saturday, 18 January 2025, 9:04 AM
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Opens: Saturday, 18 January 2025, 9:07 AM
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Registration start: Monday, 13 January 2025, 12:00 PMRegistration end: Friday, 14 February 2025, 12:00 PM
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Class Tutor's Comments Assignment
Class tutors will use this activity to provide overall feedback to students at the end of the course.
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