Extending previous efforts, this article describes how a speciating genetic algorithm is used to distribute subsets of the evolving population of solutions over the design space. This distribution of solutions is analogous to different species exploiting different niches in an ecosystem. In addition to reviewing genetic algorithms with an emphasis on techniques to cause such niche exploitation, we describe how we use statistical cluster analysis techniques to quantify the extent to which a population is speciated and how this measure can be used to probabilistically encourage mating of reasonably similar designs (i.e., intraspecies mating). Results demonstrate the creation of different good designs of characteristically different topology and shape.

1.
Chapman
C.
, and
Jakiela
M.
,
1996
, “
Genetic Algorithm-Based Structural Topology Design with Compliance and Topology Simplification Considerations
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
118
, No.
1
, pps.
89
98
.
2.
Chapman
C.
,
Saitou
K.
, and
Jakiela
M.
,
1994
, “
Genetic Algorithms as an Approach to Configuration and Topology Design
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
116
, No.
4
, pp.
1005
1012
.
3.
Chapman, C., Saitou, K., Jakiela, M., 1993, “Genetic Algorithms as an Approach to Configuration and Topology Design,” Proceedings of the ASME 19th Design Automation Conference: Advances in Design Automation, Volume 1, American Society of Mechanical Engineers, DE-Volume 65-1, New York, pps. 485–498.
4.
Deb, K., and Goldberg, D., 1989, “An Investigation of Niche and Species Formation in Genetic Function Optimization,” Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, Inc., San Mateo California, pp. 42–50.
5.
Goldberg, D., 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, Massachusetts.
6.
Goldberg, D., and Richardson, J., 1987, “Genetic Algorithms with Sharing for Multimodal Function Optimization,” Proceedings of the Second International Conference on Genetic Algorithms, Lawrence Earlbaum Associates, Hillsdale New Jersey, pp. 41–49.
7.
Holland, J., 1975, Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, Michigan.
8.
Romesburg, C., 1984, Cluster Analysis for Researchers, Lifetime Learning Publications (Wadsworth), Belmont California.
This content is only available via PDF.
You do not currently have access to this content.