We present a new faster design-style independent iterative placement improvement algorithm. Randomized simulated annealing based algorithms produce good result. But on very large designs, the inherently long run-time makes it prohibitive to use randomized algorithm. On the other hand deterministic improvement methods do not produce as good a result as the simulated annealing based algorithms. Moreover, none of the existing placement improvement techniques addresses the non row-based design style. In this paper, we combine the advantages of both the random and deterministic approach to develop a new faster placement improvement algorithm. Experimental results show that our algorithm performs much better than existing placement improvement algorithm. On some benchmarks, our algorithm is as much as 8x faster than that on Domino with a significant reduction in total net length.