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- W2097377813 endingPage "5197" @default.
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- W2097377813 abstract "Ant colony optimization (ACO) is a well-known swarm intelligence method, inspired in the social behavior of ant colonies for solving optimization problems. When facing large and complex problem instances, parallel computing techniques are usually applied to improve the efficiency, allowing ACO algorithms to achieve high quality results in reasonable execution times, even when tackling hard-to-solve optimization problems. This work introduces a new taxonomy for classifying software-based parallel ACO algorithms and also presents a systematic and comprehensive survey of the current state-of-the-art on parallel ACO implementations. Each parallel model reviewed is categorized in the new taxonomy proposed, and an insight on trends and perspectives in the field of parallel ACO implementations is provided." @default.
- W2097377813 created "2016-06-24" @default.
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- W2097377813 date "2011-12-01" @default.
- W2097377813 modified "2023-10-16" @default.
- W2097377813 title "A survey on parallel ant colony optimization" @default.
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- W2097377813 doi "https://doi.org/10.1016/j.asoc.2011.05.042" @default.
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