Genetic Algorithm was first pioneered in the 1960s by John Holland. Genetic Algorithm was applied in the search for optimal parameters. But its application is not limited to any optimization problem, it can be used for optimization problems outside. Application of genetic algorithms, among others :
Applications in optimization problems, ie for numerical optimization and combinatorial optimization such as the Traveling Salesman Problem (TSP), Integrated Circuit or IC design, Job Shop Scheduling, optimization of video, and sound.
2. Automatic Programming
Applications in automatic programming, the use of genetic algorithms in the evolutionary process for designing a computer program computational structure, such as cellular automata and sorting networks.
3. Machine Learning
Applications in machine learning, namely to design neural networks in the process of evolution of rules in learning classifier systems or symbolic production systems, as well as to control the robot.
4. Economic Model
Applications in economic models, is to model the processes of innovation and the development of bidding strategies.
5. Model Immunization System
Applications in the immunization system model, namely to model various aspects of the natural immune system, such as somatic mutation during an individual’s life and find a family with multiple genes (multi-gene families) over evolutionary time.
6. Ecological Model
Applications in ecological models, namely to model ecological phenomena such as host-parasite co-evolutions, symbiosis and the flow of resources in ecology.
7. Interaction Between Evolution and Learning
Applications in the interaction between evolution and learning, that is to learn how the process of learning an individual can affect the evolution of a species and vice versa.