Cooperative group optimization with ants (CGO-AS): Leverage optimization with mixed individual and social learning

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• 关键词：Ant systems ; Cooperative group optimization ; Traveling salesman problem ; Global optimization ; Group intelligence ; Population-based methods ; Socially biased individual learning
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：50
• 期：Complete
• 页码：223-234
• 全文大小：2663 K
• 卷排序：50

文摘

We presented CGO-AS, a generalized ant system implemented in the framework of cooperative group optimization. In CGO-AS, a novel search strategy is designed to use both individual and social cues in a controlled proportion. With CGO-AS, we expose how to leverage optimization using mixed individual and social learning. The optimization performance is tested with instances of the traveling salesman problem. CGO-AS shows a better performance than the systems which solely use either individual or social learning.