More nature-inspired heuristics

In the book

a large number of meta-heuristics based loosely on Nature are described. A list is: Simulated Annealing, Genetic Algorithms, Differential Evolution, Particle Swam Optimization, Firefly Algorithms, Cuckoo Search, Bat Algorithms, Flower Pollination Algorithms, But there are actually more to be found:

• Moth-flame optimization
• Whale Optimization
• Sine Cosine Algorithm
• Dragonfly Algorithm
• Multi-Verse Optimization
• Ant Lion Optimizer
• Grey Wolfe Optimizer
• Slime Mold Solver (apparently the favorite of Paul Rubin)
• and many more

I am note sure if the development of all these different methods is a good sign. How many should one consider or try out on a given problem?

A small collection of more interestingly named heuristics is here: http://yetanothermathprogrammingconsultant.blogspot.com/2016/08/egyptian-vultures-leaping-frogs-and.html.

References

A useful paper with a similar point of view:

Kenneth Sörensen, “Metaheuristics—the metaphor exposed,” International Transactions in Operational Research, Volume 22, Issue 1, January 2015, Pages 3–18

(Updated to reflect comments)