Haroun Mahdavi, S.; Hanna, S.; (2004) Optimising continuous microstructures: a comparison of gradient-based and stochastic methods. In: Proceedings of SCIS & ISIS 2004. The Joint 2nd International Conference on Soft Computing and Intelligent Systems and 5th International Symposium on Advanced Intelligent Systems. Keio University: Yokohama, Japan.

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Abstract

This work compares the use of a deterministic gradient based search with a stochastic genetic algorithm to optimise the geometry of a space frame structure. The goal is not necessarily to find a global optimum, but instead to derive a confident approximation of fitness to be used in a second optimisation of topology. The results show that although the genetic algorithm searches the space more broadly, and this space has several global optima, gradient descent achieves similar fitnesses with equal confidence. The gradient descent algorithm is advantageous however, as it is deterministic and results in a lower computational cost.

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