Abstract
In this study, the binary bat algorithm (BBA) for structural topology optimization is implemented. The problem is to find the stiffest structure using a certain amount of material and some constraints using the bit-array representation method. A new filtering algorithm is proposed to make BBA find designs with no separated objects, no checkerboard patterns, less unusable material, and higher structural performance. A volition penalty function for topology optimization is also proposed to accelerate the convergence toward the optimal design. The main effect of using the BBA lies in the fact that the BBA is able to handle a large number of design variables in comparison with other well-known metaheuristic algorithms. Based on the numerical results of four benchmark problems in structural topology optimization for minimum compliance, the following conclusions are made: (1) The BBA with the proposed filtering algorithm and penalty function are effective in solving large-scale numerical topology optimization problems (fine finite elements mesh). (2) The proposed algorithm produces solid-void designs without gray areas, which makes them practical solutions that are applicable in manufacturing.
Highlights
Structural optimization is considered as one of the most important fields in engineering because it can propose innovative designs that satisfy different multidiscipline design requirements
The results have shown that the binary bat algorithm (BBA) was able to surpass the binary Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) in terms of the quality of the solutions and the total number of function evaluations required to reach the optimal design [24]
The present study is an attempt to improve the quality of the solution of the topology optimization method using a large number of design variables by incorporating a new filtering algorithm and penalty function to suit the nature of the bit-array topology optimization
Summary
Structural optimization is considered as one of the most important fields in engineering because it can propose innovative designs that satisfy different multidiscipline design requirements. Over the last few decades, many metaheuristic optimization algorithms have been explored to solve complex optimization problems These methods are based on simulations, and they do not require gradient information. Metaheuristic algorithms for topology optimization usually use binary code (i.e., 0/1) to represent void/solid material distribution They can be used directly to solve structural topology optimization problems because no gray area is generated. The present study is an attempt to improve the quality of the solution of the topology optimization method using a large number of design variables (i.e., fine finite element mesh) by incorporating a new filtering algorithm and penalty function to suit the nature of the bit-array topology optimization. The numerical results of the proposed algorithm used to solve the benchmark structural topology optimization problems obtained are compared with those found using the SIMP method.
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