Metamodelling; Numerical Optimisation; Design Of Experiments
Abstract :
[en] Coupling optimisation algorithms to Finite Element Methods (FEM) is a very promising way to achieve optimal metal forming processes. However, many optimisation algorithms exist and it is not clear which of these algorithms to use. This paper investigates the sensitivity of a Sequential Approximate Optimisation algorithm (SAO) proposed in [1-4] to an increasing number of design variables and compares it with two other algorithms: an Evolutionary Strategy (ES) and an Evolutionary version of the SAO (ESAO). In addition, it observes the influence of different Designs Of Experiments used with the SAO. It is concluded that the SAO is very capable and efficient and its combination with an ES is not beneficial. Moreover, the use of SAO with Fractional Factorial Design is the most efficient method, rather than Full Factorial Design as proposed in [1-4].
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Bibliography
Bonte, M., van den Boogaard, A., and Huétink, J., "Metamodelling techniques for the optimisation of metal forming processes", Proceedings of ESAFORM, Cluj-Napoca,: Romania, 2005, pp. 155-158.
Bonte, M., van den Boogaard, A., and Huétink, J., "Solving optimisation problems in metal forming using Finite Element simulation and metamodelling techniques", Proceedings of APOMAT, Morschach, Switzerland, 2005, pp. 242-251.
Bonte, M., van den Boogaard, A., and Huétink, J., "A metamodel based optimisation algorithm for metal forming processes" accepted for Advanced Methods in Material Forming.
Bonte, M., Do, T., Fourment, L., van den Boogaard, A., Huétink, J., and Habbal, A., "A comparison of optimisation algorithms for metal forming processes" Proceedings of ESAFORM, Glasgow, UK, 2006, pp 883-886.
Nielsen, H.B., Dace, A Matlab Kriging toolbox, Technical University of Denmark, http://www.imm.dtu.dk/~hbn/dace.
Hansen, N., The CMA Evolution Strategy, Technical University of Berlin, Germany, http://lautaro.bionik.tuberlin.de/user/niko.
Emmerich, M., Giotis, A., Özdemir, M., Back, T., and Giannakoglou, K., "Metamodel-Assisted Evolution Strategies", in Parallel Problem Solving from Nature - PPSN VII, Springer-Verlag, 2002, pp 361-370.
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