Mini Map

Optimisation and operations research

MTH3330

Synopsis

This unit introduces some of the fundamental concepts and algorithms of mathematical optimisation. Optimisation underpins many parts of both data analytics (machine learning) and business analytics (management science/operations research). The concepts and approaches taught in this unit will be illustrated using examples from both types of analytics, such as training ML models and planning models arising in supply chain optimisation. The unit provides an introduction to the mathematics of continuous optimisation with focus on iterative gradient descent methods, linear programming and network optimisation. It covers both the underpinning theory, such as convergence analysis and duality, and the practical implementation of optimisation algorithms.

Sourced from the Monash Handbook 2026.

Quick facts

Credit points
6
Level
3
Audience
Undergraduate
Type
Coursework
School
Faculty of Science
Faculty
School of Mathematics
Handbook year
2026

Prerequisites (3)

What it unlocks (2)

Offerings (2)

  • First semesterClayton · ON-CAMPUS / Malaysia · ON-CAMPUS

Listed in 8 areas of study

  • Applied mathematicsLevel 3 units
  • Applied mathematicsLevel 3 units
  • Business analyticsAdditional business analytics units
  • Financial and insurance mathematicsFinancial and insurance mathematics elective unit
  • MathematicsMathematics elective units
  • MathematicsMathematics elective units
  • Pure mathematicsPure mathematics elective units
  • Mathematical statisticsAdditional elective units