An approach to continuous optimization by the Intelligent Water Drops algorithm

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• 作者：Hamed Shah-Hosseini ; ^{tasom2002@yahoo.com} ; ^{h_shahhosseini@sbu.ac.ir}
• 关键词：Optimization ; swarm intelligence ; intelligent water drops algorithm ; numerical functions ; local search ; metaheuristic
• 刊名：Procedia - Social and Behavioral Sciences
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：32
• 期：Complete
• 页码：224-229
• 全文大小：286 K

文摘

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.