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Reservoir operation optimization using adaptive varying chromosome length genetic algorithm
Two adaptive extensions of the varying chromosome length genetic algorithm (VLGA) model are proposed for optimal reservoir operation. The initial solutions for each year of the planning horizon are selected among the optimal solutions for the previous years based on the similarity in hydrologic characteristics of the years in terms of reservoir storage at the beginning of water years and annual reservoir inflows. The results from three case studies in Iran show an improvement in the convergence speed of VLGA between 21–47%. In an extended time horizon problem, the models improve the best fitness values with significantly less computation.
Reservoir operation optimization using adaptive varying chromosome length genetic algorithm
Two adaptive extensions of the varying chromosome length genetic algorithm (VLGA) model are proposed for optimal reservoir operation. The initial solutions for each year of the planning horizon are selected among the optimal solutions for the previous years based on the similarity in hydrologic characteristics of the years in terms of reservoir storage at the beginning of water years and annual reservoir inflows. The results from three case studies in Iran show an improvement in the convergence speed of VLGA between 21–47%. In an extended time horizon problem, the models improve the best fitness values with significantly less computation.
Reservoir operation optimization using adaptive varying chromosome length genetic algorithm
Zahraie, Banafsheh (author) / Kerachian, Reza (author) / Malekmohammadi, Bahram (author)
Water International ; 33 ; 380-391
2008-08-22
12 pages
Article (Journal)
Electronic Resource
Unknown
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