Shape optimization by an adaptive search genetic algorithm with biological growth strategy

Utilizing the characteristics of the adaptive search genetic algorithm and biological growth algorithm, this paper presents a hybrid approach, adaptive search genetic algorithm with biological growth strategy, for the shape optimization of structures with complicated geometry. The new algorithm embeds the biological growth algorithm into the adaptive search genetic algorithm, and therefore takes advantages of both approaches in terms of global optimization and computational efficiency. As an example of application, the new algorithm has been used for the shape optimization of three link truss and an impeller with rather complicated geometry. Being subject to the same set of geometric and stress constraints, the results show that better optimized structure in terms of weight can be achieved and the computational efficiency can also be significantly improved by the hybrid algorithm in comparison with the algorithms proposed previously.