Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the principles of adaptation. If properly engineered it is possible for SimE to reach near optimal solutions in lesser time then Simulated Annealing [1], [2]. Nevertheless, depending on the size of the problem, it may have large run-time requirements. One practical approach to speed up the execution of SimE algorithm is to parallelize it. This is all the more true for multi-objective cell placement, where the need to optimize conflicting objectives (interconnect wirelength, power dissipation, and timing performance) adds another level of difficulty [3]. In this paper a distributed parallel SimE algorithm is presented for multiobjective VLSI standard cell place...