Abstract
We propose a new population-based Evolutionary Algorithm, which uses real-coded representation and normal distribution crossover-like mutation for generating next searching points. This Gaussian distribution is formed based on the position relationships between an individual and its neighbors, and is not carried with self-adapting parameters as inheritable traits. This algorithm causes emergence of clusters of individuals within the population, as the result of evolutions of each individuals without intent to cluster. Through searching independently, that emergent clusters introduce various solutions that include optimum at the same time, even if the problem has strong local minima.
