What is Evolutionary Computing?

What is Evolutionary Computing?

Evolutionary computing is a way for a computer to solve problems by mimicking how living things evolve in real life. Just like animals and plants change over time to better survive in their environment, a computer program can improve itself to solve a task better. It’s like a computer game where the computer creates different “creatures,” and the best ones survive to create new generations… also known as “Survival of the fittest.”

Evolutionary computing is a family of computational techniques inspired by the principles of biological evolution, such as reproduction, mutation, selection, and adaptation. These techniques solve optimization and search problems by generating and manipulating a population of candidate solutions, where each candidate represents a possible solution to the problem. The population evolves through the application of genetic operators, such as crossover and mutation, that create new candidates by recombining and altering the genetic information of existing ones. The fitness of each candidate is evaluated by a fitness function that measures its quality or suitability for the problem at hand. The candidates with higher fitness are more likely to be selected for reproduction and to contribute to the next generation. In comparison, the ones with lower fitness are more likely to be eliminated from the population. This process is repeated for several generations until a satisfactory solution is found or a stopping criterion is met.