This paper presents a cellular version of Differential Evolution (DE) algorithm. The notion behind the geographical distribution of DE population with local interaction is to study the influence of slow diffusion of information throughout the population. The study was carried out using the compact configuration of neighborhood from which all the auxiliary parents for DE recombination were selected. The empirical study was carried out using a standard benchmark suite consisting of 10 functions. The results show that the structured population with local interaction improves the convergence characteristics of DE and the performance improvement was also verified using scalability study. A brief comparison with cellular GA was also included.