Direct Search Approaches Using Genetic Algorithms for Optimization of Water Reservoir Operating Policies
Publication: Journal of Water Resources Planning and Management
Volume 133, Issue 3
Abstract
The direct search approach to determine optimal reservoir operating policies is proposed with a real coded genetic algorithm (GA) as the optimization method. The parameters of the policies are optimized using the objective values obtained from system simulations. Different reservoir release rules or forms, such as linear, piecewise linear, fuzzy rule base, and neural network, are applied to a single reservoir system and compared with conventional models such as stochastic dynamic programming and dynamic programming and regression. The results of historical and artificial time series simulations show that the GA models are generally superior in identifying better expected system performance. Parsimony of policy parameters is inferred as a principle for selecting the structure of the policy, and Fourier series can be helpful for reducing the number of parameters by defining the time variations of coefficients. The proposed method has shown to be flexible and robust in optimizing various types of policies, even in models that include nonlinear, nonseparable objective functions and constraints.
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Acknowledgments
The writers would like to thank Professor Mac McKee, Director of the Utah Water Research Laboratory, for reviewing an early version of the paper.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 133 • Issue 3 • May 2007
Pages: 202 - 209
Copyright
© 2007 ASCE.
History
Received: Jan 11, 2005
Accepted: Apr 10, 2006
Published online: May 1, 2007
Published in print: May 2007
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