Interesting metaheuristic algorithms, easy to lern, many usages in real-world applications

Question

I have never been interested in optimisation. Although almost all of my professors are in it. So I have been given few subjects, which are to be used in my thesis (it is a good word?). One of them. The result should be an application. So I'm looking for an interesting metaheuristic, evolutionary algorithm, ..., that is not too hard to understand and has various usages. Maybe someone has some experience?

The topics are:

1. Differential evolution algorithms

2. Coevolution in metaheuristics
   algorithms

3. Multi ojective evolutionary algorithms ...

Answer 1

From my experience, here are some metaheuristic algorithms, ordered from easy to hard to learn and their results (again, in my experience):

1. Hill climbing - bad results

2. Tabu Search - good results

3. Great Deluge - bad results

4. Genetics algorithms - medium results

5. Simulated Annealing - very good results (if you manage to implement it correctly)