|Module code||WTW 750|
|Faculty||Faculty of Natural and Agricultural Sciences|
Classical optimisation: Necessary and sufficient conditions for local minima. Equality constraints and Lagrange multipliers. Inequality constraints and the Kuhn-Tucker conditions. Application of saddle point theorems to the solutions of the dual problem. One-dimensional search techniques. Gradient methods for unconstrained optimisation. Quadratically terminating search algorithms. The conjugate gradient method. Fletcher-Reeves. Second order variable metric methods: DFP and BFCS. Boundary following and penalty function methods for constrained problems. Modern multiplier methods and sequential quadratic programming methods. Practical design optimisation project.
|Prerequisites||Multivariate Calculus on 2nd-year level; Linear Algebra on 2nd-year level|
|Contact time||2 lectures per week|
|Language of tuition||English|
|Academic organisation||Mathematics and Applied Maths|
|Period of presentation||Semester 1|
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