Cellular manufacturing (CM) is an important application of group technology (GT) in which families of parts is produced in manufacturing cells or in a group of various machines. In this paper, a genetic algorithm approach is proposed for solving multi-objective cell formation problem. The objectives are the minimization of both total moves (intercell as well as intracell moves) and the cell load Variation. In this paper, authors used a SPEA-II method as well known and efficient standard evolutionary multi-objective optimization technique. This hybrid method presents the large set of non-dominance solutions for decision makers to making best solution. The efficiency of multi-objective GA-SPEA II is illustrated on a large-sized test problem taken from the literature.