差異進化

Differential Evolution is a stochastic optimization algorithm used for solving complex problems in product design and innovation by iteratively improving candidate solutions based on their performance. It employs a population-based approach, where potential solutions are represented as vectors and are evolved through operations such as mutation, crossover, and selection to explore the solution space effectively. This method is particularly advantageous in research and production contexts, as it can efficiently navigate multi-dimensional landscapes to identify optimal configurations and enhance design outcomes.