E19: Numerical Methods for Engineering Applications Spring 2016 - HOMEWORK 6
Single-variable unconstrained minimization
Identify a single-variable unconstrained minimization problem relevant to engineering. That is, your minimization should arise in the solution of some real-world, physicallybased design or analysis problem.
Implement one of the minimization functions we discussed in class:
- Newton's method
- Successive parabolic interpolation
- Golden section search
and use it to produce a series of 5-10 plots graphically illustrating your algorithm successfully minimizing your real-world function f(x). You can use the PdfPages backend of matplotlib to generate the plots (see https://matplotlib.org/examples/pylab examples/multipage pdf.html).
Ideally, I would like at least three students implementing each algorithm - I don't want 11 implementations of Newton's method! Therefore, please email me to receive confirmation that the algorithm you want to implement hasn't already been claimed. Also, feel free to meet with me to discuss how best to illustrate the algorithm you have chosen.
Turn in your program, along with a written description of your function and its relevance to engineering, as well as the series of plots.
Please note, you may be asked to present your problem description and plots in class sometime after spring break.