Size Optimization using Normalized Radial Basis Function and Bat Algorithm

This paper is intended to demonstrate the use of normalized radial basis function (NRBF) network and Bat Algorithm (BA) for size optimization of a mechanical part under static loading. The data needed for developing the NRBF model is generated simulating a parameterized CAD model in ANSYS Workbench 14.5. Plausible input data for the CAD model is created using Latin Hypercube Sampling (LHS) method. A torque arm is considered to proof the concept. The comparison between the result obtained from the proposed method and the solution from ANSYS Workbench itself shows that, the NRBF-BA model is indeed effective in providing a reasonable solution for a moderately complex problem.