A Review on Several Types of Crossovers Occurred in Genetic Algorithm

Genetic Algorithm (GA) is a meta-heuristic approach which can solve hybrid computation problems. In this paper, the types of crossovers used in genetic algorithm are discussed and reviewed. It was built on natural selection theory of Darwin. The genetic algorithm becomes an important part in modern technology like artificial intelligence (AI), image processing, artificial neural network (ANN), machine learning (ML), etc. The main benefit of genetic algorithm is that optimized solution for both constrained and unconstrained problem can be obtained and hence, the research community very much like to use this probabilistic optimization method or tool for analysis.