论文信息 - Topology Optimization Using An AdaptiveGenetic Algorithm And A New GeometricRepresentation

Topology Optimization Using An AdaptiveGenetic Algorithm And A New GeometricRepresentation

A new method for structural topology optimization using a genetic algorithm is proposed in this paper. This method uses a topology representation by Bézier curves with varying thickness material distribution in a finite element model. Two groups of variables are considered: control points of Bézier curves and thickness values for each curve. This new technique avoids the formation of disconnected elements and checkerboard patterns in optimal topology design. New adaptive strategies for crossover and mutation operators are also proposed. The numerical program has been developed in MATLAB and tested on a benchmark 2-D problem of topology optimization. The results obtained are compared with those obtained by the homogenization method and ANSYS code.

[1] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[2] K. Deb. An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .

[3] Carlos Artemio Coello-Coello,et al. Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art , 2002 .

[4] M. Bendsøe,et al. Generating optimal topologies in structural design using a homogenization method , 1988 .

[5] Ole Sigmund,et al. A 99 line topology optimization code written in Matlab , 2001 .

[6] Kang Tai,et al. Design of structures and compliant mechanisms by evolutionary optimization of morphological representations of topology , 2000 .

[7] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[8] James E. Baker,et al. Reducing Bias and Inefficienry in the Selection Algorithm , 1987, ICGA.

[9] M. Jakiela,et al. Continuum structural topology design with genetic algorithms , 2000 .