Optimization and Sensitivity Analysis - Math Modelling | Lecture 3

Our first modelling framework that we explore in this lecture series is optimization. In this lecture we introduce the basics of single variable optimization. Together we will work through an example that seeks to maximize profit which includes making assumptions, deriving the model, and solving the given problem. We also introduce the concept of sensitivity analysis, which describes the relative change in solutions with respect to parameter uncertainty.

This course is taught by Jason Bramburger for Concordia University.

Follow @jbramburger7 on Twitter for updates.

[morpha]

Oh my. It is incredible that we get to watch this for free. Thank you so much.

[chuckmurphy]

Amazing content, you're awesome for sharing these! One minor mistake I noticed at 17:35 - P(t) at the bottom right should be (0.65-rt)(200+5t)-0.45t (that is, +5t not -5t). Threw me for a loop later when I tried to go back and work through to the sensitivity equation from there, but found that the original parabola was upside down. Just thought it might help anyone else working along!

[niceday]

I fall in love with the lectures. wow, amazing great