Global optimisation techniques in water resources management

A. Efstratiadis, and D. Koutsoyiannis, Global optimisation techniques in water resources management, 26th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 3, Nice, doi:10.13140/RG.2.2.13774.87360, European Geophysical Society, 2001.

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[English]

Optimisation has become a valuable tool in most of hydroinformatics applications, such as calibration of hydrological models, optimal control of hydrosystems, water quantity and quality management, water supply and sewage networks design, etc. Given that these problems are intrinsically nonlinear and multimodal, they do not exist deterministic optimisation methods that can locate the globally optimal solution. During the last two decades, probabilistic schemes have been developed for solving global optimisation problems. These methods use a combination of random and deterministic steps, without generally requiring restrictive conditions on the nature of the objective function. The scope of this study is the investigation of the features of these techniques, focusing on three of them, which are presented and compared by means of both mathematical applications and real-world problems. The first two are the most popular in applications related with hydrology and water resources, i.e. genetic algorithms and the shuffled complex evolution algorithm. The third one is a new simplex-annealing scheme, which incorporates the principles of simulated annealing in the well-known downhill simplex method. This scheme is very simple to implement and extended analysis proved that it is very effective in locating the global optimum as well as very efficient, in terms of convergence speed.

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See also: http://dx.doi.org/10.13140/RG.2.2.13774.87360

Other works that reference this work (this list might be obsolete):

1. Kolovoyiannis, V. N., and G. E. Tsirtsis, Downscaling the marine modelling effort: Development, application and assessment of a 3D ecosystem model implemented in a small coastal area, Estuarine, Coastal and Shelf Science, 126, 44-60, 2013.

Tagged under: Hydrosystems, Optimization, Students' works