Artificial intelligence based optimization techniques: A review

Abstract

Many artificial intelligence based optimization techniques have been introduced since the early 60s. This paper provides a brief review of some of the well-known optimization techniques, e.g., Genetic Algorithm, Particle Swarm Algorithm, and Ant Colony Optimization and recently developed techniques, e.g., BAT Algorithm and Elephant Herding Optimization. All these techniques are population-based search algorithms, in which the initial population is created randomly initializing input parameters within the specified range. They approach toward the best solution inspired by the behavior of natural entities. All of these techniques have a potential to provide optimal or near-optimal solutions.