Memetic algorithm
Memetic algorithms are like a mix between two other types of algorithms, genetic algorithms and local search algorithms. They are used to find the best possible solution to a problem by combining the two other types of algorithms.
Genetic algorithms work by making small changes to a problem's solution over and over again until it finds the best one. This can be compared to evolution in nature, where the changes to a species are small but over time can lead to a better adapted species.
Local search algorithms work by making large changes to the problem's solution at one time. They start with a random solution and then make small adjustments to the solution until they can no longer find a better solution.
A memetic algorithm combines these two algorithms by making small changes to a problem's solution and also making larger changes to try and find the best possible solution. This way, it looks at all possible solutions, not just the ones that are close to the current solution.
Genetic algorithms work by making small changes to a problem's solution over and over again until it finds the best one. This can be compared to evolution in nature, where the changes to a species are small but over time can lead to a better adapted species.
Local search algorithms work by making large changes to the problem's solution at one time. They start with a random solution and then make small adjustments to the solution until they can no longer find a better solution.
A memetic algorithm combines these two algorithms by making small changes to a problem's solution and also making larger changes to try and find the best possible solution. This way, it looks at all possible solutions, not just the ones that are close to the current solution.