Variable Chromosome Length Genetic Algorithm for Structural Topology Design Optimization

Abstract

This article introduces the concept of variable chromosome lengths in the context of an adaptive genetic algorithm (GA). This concept is applied to structural topology optimization with large numbers of design variables. In traditional genetic algorithms, the chromosome length is determined when the phenotype is encoded into a genotype. Subsequently, the chromosome length does not change. This approach does not effectively solve problems with large numbers of design variables and complex design spaces, e.g. structural topology optimization, because the design spaces are extremely large, and it is very difficult to explore the design spaces in their entirety with reasonable population sizes. The proposed GA starts with a short chromosome and finds an optimum solution in the simple design space. The optimum solution is then transferred to the following stages with a longer chromosome while maintaining diversity in the population. More refined solutions are obtained in subsequent stages. A strain energy filter is used in order to filter out inefficiently used cells, such as protrusions or isolated islands. The variable chromosome length genetic algorithm is applied to structural topology optimization problems of a short cantilever and a bridge problem. The performance of the method is compared with a brute-force approach GA.