This paper proposes a hybrid algorithm that combines the principles of a traditional genetic algorithm enhanced with genetic screening and the exploration process of a scatter search algorithm to produce a novel approach. After the algorithm is presented, the algorithm is tested on a classic image compression problem using vector quantization. The goal is to show that this hybrid algorithm can be applied to a large class of problems such as clustering, function approximation, and optimization.