Introduction to Optimization Algorithms–Bio Inspired
Rakesh Kumar Saini, Shailee Lohmor Choudhary, Anupam Pratap Singh, Amit Verma · 2020
This chapter aims to presents a brief overview of optimization algorithms based on bio inspired techniques, namely evolutionary algorithms (EAs) and swarm intelligence algorithms, as optimization techniques which are widely used in solving complex computational problems in diversified domains like engineering, marketing, social sciences and financial modeling. EAs are algorithms based on population optimization which falls under the subfields of Evolutionary Computation, Soft Computing and Artificial Intelligence. EAs are based on natural evolution methods like reproduction, crossover, mutation and Darwin’s concept of the survival of the fittest. Under the umbrella of EAs, we have many established and widely used algorithms, such as Genetic Algorithms (GA), Genetic Programming (GP) and Gene Expression Programming. The chapter also talks about a swarm intelligence algorithm, namely Particle Swarm Optimization (PSO). In this chapter, we discover a novel classification of evolutionary procedures and discuss short descriptions of GAs, evolution techniques and their applications, and advantages as well as limitations.