Surgical simulation for medical training and education is increasingly perceived as a valuable supplement to traditional teaching methods. Recently, soft tissue modeling has become an important research area for surgical simulation and robot-assisted surgery. This area requires high-performance computing and advanced computer graphics algorithms. A majority of previous simulation methods in computer graphics use 2D or 3D meshes. Most of these approaches are based on mass-spring systems, the Finite Element Model (FEM), the Finite Difference Model (FDM) or Boundary Element Model (BEM). In mesh-based approaches, complex physical effects, such as melting, solidifying, splitting or fusion, pose great challenges in terms of restructuring the data set. Additionally, under large deformations the original meshes may become arbitrarily ill-conditioned. Mesh-free methods were developed to establish a system of algebraic equations for the whole domain without using a predefined mesh, which omits explicit connectivity information and thus solves many of the problems with mesh-based systems. This thesis proposes a Point-Based Volumetric Deformation Method (PBVD). It has the advantage that it is very suitable for tissue structure changes occurring merely during cutting and probing operations. Notably such topology changes are hard to handle utilizing mesh-based deformation models. PBVD is not only accurate because it preserves the physical material properties of the deformable object, such as Young's modulus and Poisson's ratio (as the FEM model does), but it is also faster than the FEM model. The PBVD method is developed based on an open-source frame work, SOFA, which is designed especially for surgical simulation, and makes it convenient to compare different deformation algorithms. Presented results show the high fidelity of the visual simulations generated by the PBVD method and its better real-time performance than FEM model.