A new evolutionary model designed for finding all the global and local optima of a function is proposed. Present model creates and maintains multiple subpopulations that lead at convergence each to an optimum. 
Earlier and recently, genetic chromodynamics ([5]) has provided a framework that has shown how a stepping stone search mechanism in connection with a local interaction principle (as selection for reproduction), how survival held between offspring and the stepping stone parent only and how merging between very similar chromosomes could be used as a means for the detection of multiple optima. 
The work that we present here goes further in the development of another evolutionary model in this framework. Its originality lies in several facts. The stepping stone mechanism is replaced by random selection of first parent. The offspring resulting from crossover does not fight for survival with any of its parents especially, but with the chromosome of lowest quality from its own mating region. The local interaction principle and the merging phenomenon still hold.
Though the proposed model is very simple, the experimental results conducted on several benchmark functions, i.e. Himmelblau, Six-Hump Camel Back, Schaffer and Schwefel, have demonstrated a lot of promise.