To account for this clustering effect, we introduce the concept of weighted critical area to serve as a proxy for random yield loss. A new algorithm for weighted critical area minimization is also introduced. Based on the user-specified particle densities, the proposed optimization solution is driven by the weighted critical area and dynamically selects the appropriate critical area reduction technique in each local region to guarantee a reduction of the weighted critical area in both the local region and the whole layer. This makes the algorithm flexible and readily applicable to different process lines. It consistently improves the random yield irrespective of the particle densities in the metal and empty regions of the chip.