Digital Microfluidic Biochip has emerged as a revolutionary finding in the field of micro-electromechanical research. Different complex bioassays and pathological analysis are being efficiently performed on this miniaturized chip with negligible amount of sample specimens. Initially biochip was invented on continuous-fluid-flow mechanism but later it has evolved with more efficient concept of digital-fluid-flow. These second generation biochips are capable of serving more complex bioassays. This operational change in biochip technology emerged with the requirement of high end computer aided design needs for physical design automation. The change also paved new avenues of research to assist the proficient design automation. Droplet routing is one of those major aspects where it necessarily requires minimization of both routing completion time and total electrode usage. This task involves optimization of multiple associated parameters. In this paper we have proposed a particle swarm optimization based approach for droplet outing. The process mainly operates in two phases where initially we perform clustering of state space and classification of nets into designated clusters. This helps us to reduce solution space by redefining local sub optimal target in the interleaved space between source and global target of a net. In the next phase we resolve the concurrent routing issues of every sub optimal situation to generate final routing schedule. The method was applied on some standard test benches and hard test sets. Comparative analysis of experimental results shows good improvement on the aspect of unit cell usage, routing completion time and execution time over some well existing methods.