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  3. Introduction to Optimisation

Introduction to Optimisation (ELEN90026)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

Availability
Semester 2
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AIMS

This subject provides a rigorous introduction numerical nonlinear optimization, as used across all of science and particularly in engineering design. There is an emphasis on both the theory and application of optimization techniques, with a focus on solving unconstrained and constrained nonlinear programmes. This subject is intended for research higher-degree students in engineering.

INDICATIVE CONTENT

Topics may include:

  • Algorithms for unconstrained optimization
  • Algorithms for constrained optimization
  • Convex sets and functions
  • Convex optimization problems
  • Duality theory
  • Computational complexity
  • Approximation algorithms and penalty methods.

Intended learning outcomes

INTENDED LEARNING OUTCOMES (ILOs)


Having completed this subject it is expected that the student be able to:



  • Demonstrate an in-depth understanding of numerical linear algebra and real analysis within the context of optimization problems
  • Formulate and solve engineering problems via nonlinear optimisation methods
  • Apply computational tools to solve standard unconstrained and constrained optimization problems.

Generic skills

On completion of this subject, students will have developed the following skills:

  • Ability to apply knowledge of basic science and engineering fundamentals;
  • In-depth technical competence in at least one engineering discipline;
  • Ability to undertake problem identification, formulation and solution;
  • Ability to utilise a systems approach to design and operational performance;
  • Expectation of the need to undertake lifelong learning, capacity to do so;
  • Capacity for independent critical thought, rational inquiry and self-directed learning;
  • Profound respect for truth and intellectual integrity, and for the ethics of scholarship.

Last updated: 3 November 2022