FIT5216 Modelling discrete optimisation problems
Faculty of Information Technology
FIT5216 Modelling discrete optimisation problems is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology, offered in 2020 in Semester 1 at Clayton and Suzhou (SEU). It needs FIT9136, FIT9131 or FIT9133 and unlocks 1 unit.
- Credit points
- 6
- Offered in 2020
- Semester 1
- Clayton, Suzhou (SEU)
- Workload
- 12 hours
- per semester
This is the 2020 handbook entry. See the 2027 entry.
Reviews
No reviews yetNo reviews yet. Be the first to review FIT5216.
Requisites
Before FIT5216
Prerequisites
Pass these before you enrol.
After FIT5216
1 unit list FIT5216 as a prerequisite or corequisite.
Enrolment rules
Prerequisite: For students enrolled in C6007 - None.
Overview
This unit introduces the fundamentals of modelling for discrete optimisation, focusing on how to rigorously express a discrete optimisation problem in a manner that is can be solved. Topics covered will include decision variables, basic constraints, modelling with sets, modelling with functions, multiple modelling viewpoints, modelling time, common modelling patterns, model translation, and debugging discrete optimisation models. We will examine complex real world problems and see how they can be translated so that they can be solved by modern discrete optimisation technology.
Offerings in 2020
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | On campus |
| First semester | Suzhou (SEU) | On campus |
| First semester (Fully flex) | Clayton | Flexible |
Learning outcomes
When you finish this unit, you should be able to:
- 1
model a discrete optimisation problem using a mix of basic and more advanced modelling techniques in a high level modelling language;
- 2
interpret and explain models written by others;
- 3
explain how models are mapped to solver-level input;
- 4
identify and fix errors in models;
- 5
evaluate the limitations, appropriateness and benefits of different modelling patterns for common problem classes;
- 6
evaluate and improve the efficiency of models by applying different model transformations.
Workload and teaching
Minimum total expected workload equals 12 hours per week comprising:
- Two hours/week workshops
- Two hours/week laboratories
A minimum of 8 hours per week of personal study for completing lab activities, assignments, private study and revision.
Where it fits
FIT5216 is part of 1 area of study in the 2020 handbook.
Contacts
- Chief Examiners
- Dr Guido Tack
Common questions
What are the prerequisites for FIT5216?
You need FIT9136, FIT9131 or FIT9133 before you enrol. Enrolment rules also apply.
What can I take after FIT5216?
FIT5216 is a prerequisite or corequisite for 1 unit, including FIT5220.
When is FIT5216 offered?
In 2020, FIT5216 runs in Semester 1 at Clayton and Suzhou (SEU).
How much work is FIT5216?
The handbook expects about 12 hours of study across the semester. No students have rated its difficulty yet.
Which majors and minors include FIT5216?
FIT5216 is part of Software engineering.