Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1123001 | Procedia - Social and Behavioral Sciences | 2012 | 6 Pages |
Abstract
In this paper, the Intelligent Water Drops (IWD) algorithm is augmented with a mutation-based local search to find the optimal values of numerical functions. The proposed algorithm called the IWD-CO (IWD for continuous optimization) is tested with six different benchmark functions. The experimental results are satisfactory, which encourage further researches in this regard.
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