The University of Newcastle, Australia
Available in 2019

Course handbook

Description

Broadly speaking, mathematical optimisation refers to the selection of the 'best' element from an available set. The subject is fundamental in numerous scientific, financial and engineering applications and is an extremely active area of current research. This course introduces students to the fundamental analytical and computational techniques of mathematical optimisation. It provides students with the skills to formulate real-world problems in the language of optimisation, to solve these problems and to analyse the solutions.


Availability2019 Course Timetables

Callaghan

  • Semester 1 - 2019

Replacing course(s)

This course replaces the following course(s): MATH2730 and MATH3830. Students who have successfully completed MATH2730 or MATH3830 are not eligible to enrol in MATH3800.


Learning outcomes

On successful completion of the course students will be able to:

1. Formulate real-world problems in the mathematical language of optimisation

2. Solve problems using analytical and computational techniques

3. Interpret solutions of optimisation problems as they apply to scientific, financial and industrial applications


Content

  • Foundations of Optimisation
  • Linear Programming
  • Unconstrained Optimisation
  • Nonlinear Optimisation

Requisite

Students must have successfully completed MATH1510 and MATH2310 to enrol in this course. Students cannot enrol in this course if they have previously successfully completed MATH2730 and/or MATH3830.


Assessment items

Formal Examination: Formal Examination

Written Assignment: Written Assignments


Contact hours

Callaghan

Computer Lab

Face to Face On Campus 1 hour(s) per Week for 11 Weeks

Lecture

Face to Face On Campus 2 hour(s) per Week for 12 Weeks

Workshop

Face to Face On Campus 1 hour(s) per Week for 12 Weeks