Bat algorithm as a metaheuristic optimization approach in materials and design: optimal design of a new float for different materials

An application of bat algorithm (BA) as a metaheuristic optimization approach in materials and design to an engineering problem has been presented in this paper. The purpose of the case study was to develop a new float as a part of measurement system according to the setup configuration and test environment. With this regard, several materials such as Acrylic, PVC, Nylon, Teflon (PTFE), and low-density polyethylene as feasible options for the float body in terms of mechanical, thermal, and chemical properties were selected. Then, optimal concurrent design of the float system with selected materials based on structural and performance constraints was addressed. For this purpose, the design was formulated into a constrained optimization problem and BA was used to find the optimal solutions in order to minimize the float length. The convergence of the design variables and constraints to optimal values was also investigated. Generalized reduced gradient method was used as well for validation and comparison of the BA results. It was found that the new optimal float had a pretty good performance in the test measurement. The results showed that BA can be a quite efficient approach to solve constrained optimization problems in materials and design. It is also suggested that the new float problem can be considered as a benchmark problem in materials and design to validate the robustness of the optimization algorithms.