Memetic Algorithms

Memetic Algorithms are advanced optimization methods that combine evolutionary techniques, like genetic algorithms, with local problem-solving strategies. They mimic natural selection to generate a diverse set of solutions and then refine these solutions through focused, problem-specific improvements. This approach accelerates finding high-quality solutions by blending broad exploration of possibilities with detailed exploitation of promising options. Memetic algorithms are useful in complex problems where traditional methods struggle, as they balance global search and local refinement efficiently.