ABSTRACT
In the field of data analytics algorithms, meta-heuristic algorithms are deployed in different areas. A meta-heuristic algorithm has two main features of “intensification” and “diversification”, or “exploitation” and “exploration”. Nature-inspired algorithms divide into two groups: evolutionary and swarm intelligence. The first is related to Darwin’s evolutionary theory. The second considers the natural behaviour of creatures. They are powerful and popular sources which have become the focus of much research in recent decades. Genetic algorithms (GA) has been introduced as a randomised search that aims to find near-optimal solutions to problems with a high level of complexity and dimension. The main parameter in GA that is considered in space searches is chromosomes with string shape. Ant colony optimisation has been introduced as a population-based stochastic method. The method imitates real ant behavior in the process of searching for food. A bionic algorithm will be chosen to find the optimal solution.
