Using a hybrid genetic algorithm–simulated annealing algorithm for fuzzy programming of reservoir operation
Journal
Hydrological Processes
Journal Volume
21
Journal Issue
23
Start Page
3162
End Page
3172
ISSN
0885-6087
1099-1085
Date Issued
2007-10-18
Author(s)
Abstract
We present a novel approach for optimizing reservoir operation through fuzzy programming and a hybrid evolution algorithm, i.e. genetic algorithm (GA) with simulated annealing (SA). In the analysis, objectives and constraints of reservoir operation are transformed by fuzzy programming for searching the optimal degree of satisfaction. In the hybrid search procedure, the GA provides a global search and the SA algorithm provides local search. This approach was investigated to search the optimizing operation scheme of Shihmen Reservoir in Taiwan. Monthly inflow data for three years reflecting different hydrological conditions and a consecutive 10-year period were used. Comparisons were made with the existing M-5 reservoir operation rules. The results demonstrate that: (1) fuzzy programming could effectively formulate the reservoir operation scheme into degree of satisfaction α among the users and constraints; (2) the hybrid GA-SA performed much better than the current M-5 operating rules. Analysis also found the hybrid GA-SA conducts parallel analyses that increase the probability of finding an optimal solution while reducing computation time for reservoir operation. Copyright © 2007 John Wiley & Sons, Ltd.
Subjects
genetic algorithm
simulated annealing
hybrid GA-SA
reservoir operation
fuzzy programming
Publisher
Wiley
Type
journal article