Abstract
Many of the problems encountered in engineering may be reformulated as optimisation problems but often the corresponding objective function may be highly nonlinear or non-monotonie, may have a very complex form or its analytical expression may be unknown. Traditional, gradient based, optimisation algorithms are likely to fail for objective functions that exhibit multiple local optima and for such a gradient based algorithms in practice it is often difficult to provide an initial guess which is within the radius of convergence towards the global optimum. Also, in order to achieve convergence various restrictions are imposed and the applicability of such gradient algorithms is limited since these requirements are rarely met in practice. Moreover, gradient computations may constitute a problem in itself if noise is present in the measurements. Therefore, for complex practical problems, often it is required to use a more robust and adaptive approach.
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Mera, N.S., Ingham, D.B., Elliott, L. (2004). Genetic Algorithms and their Application to the Identification of Hydraulic Properties of Rocks. In: Ingham, D.B., Bejan, A., Mamut, E., Pop, I. (eds) Emerging Technologies and Techniques in Porous Media. NATO Science Series, vol 134. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0971-3_8
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DOI: https://doi.org/10.1007/978-94-007-0971-3_8
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