MATH3171: Linear and Discrete Optimization Modelling

- 0% quiz (Guoyin wanted to provide initial feedback in Week 3. He did this for us in case some of us felt like dropping, which was really nice.)
- 2 x 15% tests
- 10% assignment
- 60% final exam

Either one of the following:
- MATH2011/2111 and MATH2501/2601
- MATH2069 (CR) and MATH2099
- MATH2018/2019 (DN) and MATH2089

This is one of many Level 3 elective courses under applied mathematics. Note that this year was the first time ever this course was run, i.e. it was a brand new course.

When I asked A/Prof Guoyin to compare this course to MATH3161, he felt that the main differences were in that:
- The content in this course is mostly quite new. And indeed so; the field of conic programming is something that's only been around for a few decades.
- Interestingly, this course does have more of a focus on global extrema, whilst MATH3161 builds on local extrema techniques.

The courses are complementary; they have similar focuses but different executions. I would advise any student interested in optimisation to try taking both of them at some point.

This course was generally speaking quite relaxing. I found most of the concepts quite straightforward to learn, and although I was quick to forget it all, it also came back quickly whilst studying for an upcoming assessment task. But what I really liked was how so many concepts took me by surprise. They're not things I would've ever thought of in solving any optimisation problem. The course felt really fresh in that regard.

Assessment tasks were generally speaking quite straightforward, apart from the first 15% test that I ran out of time in. I don't believe the course was inherently easy, but it definitely was on the more relaxing end of the spectrum.

2 x 2hr lectures, 1hr tutorial

2.5/5

Yes

A/Prof Guoyin Li

Lecture notes and tutorial problems were enough. (He also provides optional additional reading.)

4/5

N/A

19t3

95 HD