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• W5746818 abstract "Real-life water resource problems such as optimal allocation of scare water, watershed management, conjunctive use of surface and groundwater, reservoir operation, water distribution systems, and management of water quality have many complex features. The variables involved may be discrete, discontinuous, or both; frequently the variables are stochastic and highly nonlinear. These typical problems limit the use of traditional nonlinear algorithms, such as the gradient-based algorithms, since the solution may converge to local optima and the computational requirements may be very high. Evolutionary algorithms, such as genetic algorithms (GAs), do not rely on any mathematical properties of the functions employed in the model. This feature makes them robust and more generally applicable than the other directed search methods. GAs are a particular class of evolutionary algorithm based on mechanics of natural selection and natural genetics, and they use techniques inspired by evolutionary biology such as inheritance, mutation, selection, crossover, and survival of the fittest. Since GAs are heuristic search techniques, the global optimum solution is not guaranteed. Nevertheless, GAs give alternative solutions that are close to the optimum after a reasonable number of evolutions, which is acceptable for most real-life problems. This chapter introduces the art and applications of GAs to water resource optimization problems. An illustrative example of reservoir operation optimization has been included to clarify the concepts." @default.
• W5746818 created "2016-06-24" @default.
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• W5746818 creator A5017131679 @default.
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• W5746818 creator A5072522918 @default.
• W5746818 date "2013-01-01" @default.
• W5746818 modified "2023-09-24" @default.
• W5746818 title "Genetic Algorithms and Their Applications to Water Resources Systems" @default.
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• W5746818 doi "https://doi.org/10.1016/b978-0-12-398296-4.00003-9" @default.
• W5746818 hasPublicationYear "2013" @default.
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