How to Design Optimization Algorithms by Applying Natural Behavioral Patterns

Nature and Optimization Algorithms

Author(s): Rohollah Omidvar* and Behrouz Minaei Bidgoli *

Pp: 7-13 (7)

DOI: 10.2174/9789811459597121010005

* (Excluding Mailing and Handling)


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.

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