Go to Courses and units

Modelling and Optimisation unit (KMA355)

eStudent Enquire

Unit year 2027

View 2026 unit information

View previous years unit information

Related units

Quick Help

Location: Hobart

Introduction

This unit equips students with skills in modelling and optimising real world systems using discrete-state-space models and modern optimisation methods. These approaches are fundamental for analysing systems that evolve over time, particularly under uncertainty. Throughout the unit, you will develop strong problem solving and analytical skills through models and algorithms in Dynamic Programming, Markovian Decision Processes, Queueing Theory, and Simulation. You will learn to apply these methods to practical decision making and planning problems, and solve them using advanced numerical and computational tools. This unit is a core unit within the Statistics and Decision Science major (Bachelor of Science).

Summary

Unit name Modelling and Optimisation
Unit code KMA355
Credit points 12.5
College/School Sciences and Engineering
School of Natural Sciences
Discipline Mathematics
Coordinator Associate Professor Malgorzata O'Reilly
Available as an elective? Yes
Delivered By
Level Advanced

Availability

Location Study period Attendance options Available to
Hobart Semester 2 This unit is available through on-campus delivery Available to International Students Available to Domestic Students
  • Key:
  • This unit is available through on-campus delivery On-campus
  • This unit is available through off-campus delivery Off-Campus
  • Available to International Students International students
  • Available to Domestic Students Domestic students
Note

Please check that your computer meets the minimum System Requirements if you are attending via Distance/Off-Campus.

Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.

Key Dates

Study Period Start date Census date WW date End date
Semester 2 05/07/2027 27/07/2027 30/08/2027 24/10/2027

* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).

Unit census dates currently displaying for 2027 are indicative and subject to change. Finalised census dates for 2027 will be available from the 1st October 2026. Note census date cutoff is 11.59pm AEST (AEDT during October to March).

About Census Dates

Learning Outcomes

  • Construct models using Dynamic Programming, Queueing Theory, and Simulation to represent real-world systems.
  • Apply analytical and problem-solving techniques from Dynamic Programming, Queueing Theory, and Simulation to perform numerical analysis of real-world problems.
  • Explain modelling and optimisation methods using mathematical language and notation.
  • State and use formal definitions and properties of fundamental mathematical structures relevant to modelling and optimisation.

Fee Information

Field of Education Commencing Student Contribution 1,3 Grandfathered Student Contribution 1,3 Approved Pathway Course Student Contribution 2,3 Domestic Full Fee 4
010101 $613.00 $613.00 not applicable
  • Available as a Commonwealth Supported Place
  • HECS-HELP is available on this unit, depending on your eligibility3
  • FEE-HELP is available on this unit, depending on your eligibility4

1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.

If you have any questions in relation to the fees, please contact UniConnect or more information is available on StudyAssist.

Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.

Requisites

Prerequisites

Any intermediate (200 coded) KMA unit

Teaching

Teaching Pattern

Face to face:

1-hr/week pre-recorded video lectures, 1-hr/week online lecture, 1-hr/week tutorial, 1-hr/week lab, 1-hr/week optional online Q&A

Online:

1-hr/week pre-recorded video lectures, 1-hr/week online lecture, 1-hr/week online tutorial/lab, 1-hr/week optional online Q&A

AssessmentDemonstration (10%)|Examination (40%)|Assignment (multiple) (50%)
TimetableView the lecture timetable | View the full unit timetable

Textbooks

Required

Required readings will be listed in the unit outline prior to the start of classes.
Recommended

• S. M. Ross, Introduction to Probability Models.
• Taha, H.A., Operations Research: An Introduction.
• Winston, W. L., Operations Research: Applications and Algorithms.
• W. Feller, An Introduction to Probability Theory and Its Applications, vol. I.

The University reserves the right to amend or remove courses and unit availabilities, as appropriate.