This paper discusses the parallelization of Stochastic Evolution (StocE) metaheuristic, for a distributed parallel environment. VLSI cell placement is used as an optimization problem. A comprehensive set of parallelization approaches are tested and an effective strategy is identified in terms of two underlying factors: workload division and the effect of parallelization on metaheuristic's search intelligence. The strategies are compared with parallelization of another similar evolutionary metaheuristic called Simulated Evolution (SimE). The role of the two mentioned underlying factors is discussed in parallelization of StocE.