ABSTRACT
In previous chapters, we covered sets of modern numerical swarm-based optimization methods including:
• Bat algorithm (BA) • Firefly algorithm (FFA) • Cuckoo search (CS) • Flower pollination algorithm (FPA) • Artificial bee colony (ABC) • Artificial fish swarm algorithm (AFSA) • Wolf search algorithm (WSA) • Gray wolf optimization (GWO)
In this chapter, we are trying to classify the above algorithms according to different criteria and find similarities and differences based on these criteria. This discussion may help in finding weak and strong points of each and may help in presenting new hybridizations and modifications to further enhance their performance or at least help us choose among this set to handle specific optimization tasks.
