Abstract
This paper uses genetic algorithm to handle the topology and sizing optimization of truss structures, in which a sparse node matrix encoding approach is used and individual identification technique is employed to avoid duplicate structural analysis to save computation time. It is observed that NSGA-II could not improve the convergence of non-dominated front at latter generations when solving multi-objective topology and sizing optimization of truss structures. Therefore, an adaptive multi-island search strategy for multi-objective optimization problem (AMISS-MOP) is developed to enhance the convergence. Meanwhile, an elitist strategy based on archive set is introduced to reduce the size of non-dominated sorting to improve computation efficiency. Two numeric examples are presented to demonstrate the performance of AMISS-MOP. Results show that the global Pareto front could be found by AMISS-MOP, the convergence is improved as generation increases, and the time spent on non-dominated sorting is reduced.
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Acknowledgements
This work was supported in part by the National High Technology Research and Development Program (“863” Program) of China under Grant no. 2007AA04Z133. The authors are grateful to the support.
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Su, R., Wang, X., Gui, L. et al. Multi-objective topology and sizing optimization of truss structures based on adaptive multi-island search strategy. Struct Multidisc Optim 43, 275–286 (2011). https://doi.org/10.1007/s00158-010-0544-4
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DOI: https://doi.org/10.1007/s00158-010-0544-4