Inclusive and Relative Analysis of Nature Inspired Optimization Algorithms in Reference to Sworn Intelligence

This article provides many nature-inspired algorithms and discusses their characteristics as well as the methods by which they are implemented. This study is an effort to determine the optimal searching algorithm in terms of the number of search agents in a given population. With a dataset and an increasing population size, the parameter of execution time for searching algorithms is examined by the researchers. This comparative research aims to give a more comprehensive knowledge of Nature inspired optimization algorithms (NIOAs) by providing a larger viewpoint and deliberate illumination. This paper provides the pseudocodes of the selected algorithms.