Investigation of Artificial Intelligence Based Optimization Algorithm

In this study, the concept of artificial intelligence (AI), deep learning and machine learning are explained and the relation between AI and optimization algorithms are examined. By defining the basic stages and the content of deep learning and machine learning, the relationship of AI with optimization is investigated. In the light of this study, four optimization algorithms were considered. The steps and the operations of these artificial intelligence-based optimization algorithms which were widely used in the literature have been examined in detail. All the algorithms discussed in this study are related to nature. These algorithms are; Bacterial Foraging Optimization, Flower Pollination Optimization, Genetic Algorithm and Artificial Bee Colony Algorithm. The studies in the literature carried out by modelling the life cycle of bacteria known as koli basil in Bacterial Foraging, the pollination event in flower pollination plants in Flower Pollination, genetics in Genetic Algorithm and the formation of genes that lead to the formation of a high quality population and bees' behavioural logic in Artificial Bee Colony. While the studies except the Artificial Bee Colony were the direct models of the phenomenon in nature, the Artificial Bee Colony was put forward by adding a comment about how the behaviours of bee colonies can be separated from the expected and unexpected values in a sample space. In this study, the stages of all these algorithms and the logic used in each step are examined. Some recent important application domains related to these algorithms are also discussed. In the conclusion part, what can be done in the light of these studies as a future work is mentioned