Genetic Algorithms As an Approach to Configuration and Topology Design

Abstract

Abstract The Genetic Algorithm, a search and optimization technique based on the theory of natural selection, is applied to problems of structural topology optimization. Given a structure’s boundary conditions and maximum allowable design domain, a discretized design representation is created. Populations of genetic algorithm “chromosomes” are then mapped into the design representation, creating potentially optimal structure topologies. Utilizing genetics-based operators such as crossover and mutation, generations of increasingly-desirable structure topologies are created. In this paper, the use of the genetic algorithm (GA) in structural topology optimization is presented. An overview of the genetic algorithm will describe the genetics-based representations and operators used in a typical genetic algorithm search. After defining topology optimization and its relation to the broader area of structural optimization, a review of previous research in GA-based and non-GA-based structural optimization is provided. The design representations, and methods for mapping genetic algorithm “chromosomes” into structure topology representations, are then detailed. Several examples of genetic algorithm-based structural topology optimization are provided: we address the optimization of beam cross-section topologies and cantilevered plate topologies, and we also investigate efficient techniques for using finite element analysis in a genetic algorithm-based search. Finally, a description of potential future work in genetic algorithm-based structural topology optimization is offered.