MATH3002

MATH3002: Numerical Optimisation

Science and Engineering

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About this Unit

This unit introduces the fundamental techniques and methods for solving optimisation and numerical optimisation problems. Topics will cover optimisations models, one-dimensional search techniques, unconstrained optimisation techniques including steepest descent method, Newton’s method, conjugate gradient methods, and constrained optimisation techniques including Lagrangian multipliers, Kuhn-Tucker optimality conditions, sequential quadratic programming.

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Unit Details

Credits25

Contact Hours4 Weekly

Result TypeGrade/Mark

AreaSchool of Electrical Engineering, Computing and Mathematical Sciences (EECMS) (1153)

Field of Education010101 Mathematics

Handbook View Official Handbook Page →

Tuition Pattern

Lecture1 x 2 hours weekly
Tutorial1 x 1 hour weekly
Workshop1 x 1 hour weekly

Prerequisites

PrerequisitesSelect One

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