Genetic Algorithm-Based Structural Topology Design With Compliance and Topology Simplification Considerations

1996 ◽  
Vol 118 (1) ◽  
pp. 89-98 ◽  
Author(s):  
C. D. Chapman ◽  
M. J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Optimization Technique ◽  
Topology Design ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Design Representation ◽  
Homogenization Methods ◽  
Future Work ◽  
Structural Topology Design

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.

scholarly journals Genetic Algorithms as an Approach to Configuration and Topology Design

1994 ◽  
Vol 116 (4) ◽  
pp. 1005-1012 ◽  
Author(s):  
C. D. Chapman ◽  
K. Saitou ◽  
M. J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Optimization Technique ◽  
Topology Design ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Design Representation ◽  
Future Work ◽  
Structural Topology Design ◽  
Algorithm Search

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.

Genetic Algorithm-Based Structural Topology Design With Compliance and Manufacturability Considerations

1994 ◽  
Author(s):  
Colin D. Chapman ◽  
Mark J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Optimization Technique ◽  
Weight Ratio ◽  
Topology Design ◽  
Structural Topology ◽  
Programming Technique ◽  
Design Representation ◽  
Homogenization Methods ◽  
Future Work ◽  
Structural Topology Design

Abstract 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.

scholarly journals Genetic Algorithms As an Approach to Configuration and Topology Design

1993 ◽  
Author(s):  
Colin D. Chapman ◽  
Kazuhiro Saitou ◽  
Mark J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Structural Optimization ◽  
Optimization Technique ◽  
Topology Design ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Element Analysis ◽  
Structure Topology ◽  
Design Representation

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.

scholarly journals Structural Topology Design Optimization Using the Binary Bat Algorithm

2020 ◽  
Vol 10 (4) ◽  
pp. 1481 ◽  
Author(s):  
Abdulkhaliq A. Jaafer ◽  
Mustafa Al-Bazoon ◽  
Abbas O. Dawood
Keyword(s):  
Topology Optimization ◽  
Penalty Function ◽  
Large Scale ◽  
Optimization Problems ◽  
Bat Algorithm ◽  
Topology Design ◽  
Benchmark Problems ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Filtering Algorithm

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.

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