Recently, we have introduced Multi-Leader Particle Swarm Optimization (MLPSO) algorithm for multiobjective optimization problem. Better convergence and diversity have been observed over the conventional MultiObjective Particle Swarm Optimization. In this paper, the same concept is extended to Gravitational Search Algorithm (GSA). The performance was investigated by solving a set of ZDT test problem. An analysis was also performed by varying the value of initial gravitational constant.