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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 to 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 graduate and research higher-degree students in engineering.

INDICATIVE CONTENT

Topics 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

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

  • Apply 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: 8 November 2024