New algorithms have been developed to see if they can cope with these
challenging optimization problems. Among these new algorithms, many algorithms,
such as particle swarm optimization, cuckoo search, and firefly algorithm, have gained
popularity due to their high efficiency. In the current literature, there are about 40
different algorithms. It is a challenging task to classify these algorithms systematically.
In this chapter, the reader becomes familiar with the source of nature so that he can
come up with an idea. Therefore, the first step in building and delivering a natureinspired
algorithm is to become familiar with nature and understand its features. Nature
is a great source of inspiration for all stages of human life. In nature, creatures and
structures always find solutions to their problems. Hence, it is nature that plays the
leading role. Nature-inspired optimization algorithms are always some of the best
mechanisms to solve complex problems. In this chapter, the reader will be introduced
to a variety of nature-based optimization algorithms. Optimization algorithms are
introduced and their techniques will be examined. This chapter has a history of natureinspired
algorithms whose evolution is visible. Researchers have tried to draw
inspiration from natural resources as well as animals from nature that provided
algorithms that have helped researchers in many problems. This chapter can also
introduce readers to the history of making nature-based algorithms.
Keywords: Algorithm, Cost, Meta-heuristic, Nature, Optimization, Problem.