<p>The sensing and manipulation of objects through sense of touch is called haptics and a haptic device is a robotic interface through which human user can interact physically with objects in a remote or virtual environment. An important application of haptics is surgical simulator for medical practitioners, where development of models of tool-tissue interaction that are realistic and real-time is the primary challenge. Despite availability of many methods, mass-spring system (MSS) and finite element method (FEM) are quite popular and typically used as simulation methods for haptic rendering of soft tissue modeling. Since MSS is the simplest physical model comparatively, it is an appropriate choice for designing real-time simulations. However, the identification of optimum system parameters such as mesh topology, stiffness &amp; damping coefficient of springs, and nodal masses is the major challenge in using MSS for simulation of deformable objects. In this work, we have used a genetic algorithm (GA) based data driven method for identification of mesh topology of MSS and observed that mesh topologies identified by GA approximate closely deformation of reference FEM models in tension, but there is considerable percentage error in shear and compression. Also, the complete procedure of mesh topology identification has to be repeated, if a change in the mesh topology is required for a particular application. We further observed that there is need for simultaneous identification of mesh topology as well as spring stiffness for MSS model.</p>