Automated grasp planning for robotic hands is a complex problem when compared with the ease with which human hands grasp objects. Research in robotic grasp synthesis attempts to find novel ways in which a stable grasp can be achieved reliably. In this work, we present a grasping methodology that achieves optimized force closure grasps on 3D irregular objects. 3D objects in the form of polygonal meshes are parameterized to 2D shapes in order to reduce the search space by constraining robotic hands finger tips to be in contact with the objects surface. We use a Particle Swarm Optimization (PSO) based framework to optimize an initial grasp. The scheme has been validated on test-case 3D objects represented with surface tessellation for a 5-fingered DLR robotic hand.