The genetic algorithm, a search and optimization technique based on the theory of natural selection, is applied to problems of structural topology design. An overview of the genetic algorithm will first describe the genetics-based representations and operators used in a typical genetic algorithm search. Then, a review of previous research in structural optimization is provided. A discretized design representation, and methods for mapping genetic algorithm “chromosomes” into this representation, is then detailed. Several examples of genetic algorithm-based structural topology optimization are provided: we address the optimization of cantilevered plate topologies, and we investigate methods for optimizing finely-discretized design domains. The genetic algorithm’s ability to find families of highly-fit designs is also examined. Finally, a description of potential future work in genetic algorithm-based structural topology optimization is offered.
The genetic algorithm (GA), an optimization technique based on the theory of natural selection, is applied to structural topology design problems. After reviewing the GA and previous research in structural topology optimization, we describe a binary material/void design representation that is encoded in GA chromosome data structures. This representation is intended to approximate a material continuum as opposed to discrete truss structures. Four examples, showing the broad utility of the approach and representation, are then presented. A ®fth example suggests an alternate representation that allows continuously-variable material density. Concluding discussion suggests recommended uses of the technique and describes ongoing and possible future work. Ó 2000 Elsevier Science S.A. All rights reserved.
The genetic algorithm (GA), an optimization technique based on the theory of natural selection, is applied to structural topology design problems. After reviewing the genetic algorithm and previous research in structural topology optimization, we detail the chromosome-to-design representation which enables the genetic algorithm to perform structural topology optimization. Extending our prior investigations, this article first compares our genetic-algorithm-based technique with homogenization methods in the minimization of a structure’s compliance subject to a maximum volume constraint. We then use our technique to generate topologies combining high structural performance with a variety of material connectivity characteristics which arise directly from our discretized design representation. After discussing our findings, we describe potential future work.
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.
The genetic algorithm, a search and optimization technique based on the theory of natural selection, is applied to structural topology design problems with compliance and manufacturability considerations. After describing the genetic algorithm and reviewing previous research in structural topology design, we detail the chromosome-to-design representation which enables the genetic algorithm to perform structural topology optimization. Extending our prior investigations, this article details the use of our genetic algorithm-based technique to minimize a structure’s compliance, subject to a maximum volume constraint. The resulting structure is then directly compared with a solution obtained using a mathematical programming technique and material homogenization methods. We also demonstrate how our technique can generate structures which combine high stiffness-to-weight ratio with high manufacturability. After a brief discussion of our findings, we describe potential future work in genetic algorithm-based structural topology design.
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