Almost inevitably, in this third chapter on evolutionary optimization, an inquietude emerges: more algorithms? What is the best one? A cruel reality is shown by the no-free-lunch theory, introduced in the beginning of this chapter. What we could say here is that the effectivity of any heuristic approach depends on properly capturing as much as possible the “a priori” knowledge you have on the problem at hand; and this capture is more or less facilitated by this or another algorithm or metaphor. This chapter wants to extend the variety of methods considered. The result is an assortment of different metaphors: artificial immune systems, harmony search, imperialist competitive algorithm, gravitational search algorithm, sine cosine algorithm, biogeography-based optimization, flower pollination algorithm, fireworks algorithm, and mine blast algorithm. You could use the MATLAB programs included in the chapter, for personal exploration and experimentation.