I'd recommend also implementing the DIRECT algorithm, which balances local and global search very well (but consequently will not refine as aggressively near the current [possibly only local] optimum as other algorithms):

https://www.researchgate.net/profile/Donald-Jones-5/publicat...

You probably also want to include some advantages/disadvantages of each algorithm. How robust against local minima is it? Up to how many dimensions does it work well? How is the convergence speed when started far from the optimum? Does it work well with few function evaluations? Etc.