Abstract
We present the efficiency of various probabilistic algorithms, including the standard genetic algorithm, micro-genetic algorithm, evolutionary strategy, randomly initialized hill climbing, and mutation based algorithms for the optimization of electromagnetic devices operating at microwave and optical frequencies. Single fitness evaluations are costly because the electromagnetic field computation time is usually long. We therefore need to find strategies that provide optimal solutions in under a few hundred fitness evaluations. This constraint considerably affects the design of the optimizer. In order to obtain reliable guidelines, various optimization algorithms have been applied to three optimization problems.
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Smajic, J., Mishrikey, M., Fallahi, A., Hafner, C., Vahldieck, R. (2008). Efficiency of Various Stochastic Optimization Algorithms in High Frequency Electromagnetic Applications. In: Krasnogor, N., Nicosia, G., Pavone, M., Pelta, D. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Studies in Computational Intelligence, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78987-1_24
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DOI: https://doi.org/10.1007/978-3-540-78987-1_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78986-4
Online ISBN: 978-3-540-78987-1
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