Ant colony optimization
Ant colony optimization
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DOI：
10.1145/2001858.2002122
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发表时间：
2011-07
期刊：
影响因子：
--
通讯作者：
Marco Dorigo;M. Birattari
中科院分区：
文献类型：
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作者：
Marco Dorigo;M. Birattari
蚁群优化算法是模拟蚁群行为的一种新的自然计算方法。这是一种非常好的组合优化方法。蚁群优化算法是新近提出的一种算法，它具有较强的鲁棒性以及良好的分布式计算机制，并且易于与其他方法相结合，在解决复杂的优化问题上表现出了良好的性能。提出了一种求解资源受限项目调度问题的蚁群优化算法。以旅行商问题为例，介绍了蚁群算法的基本原理，并针对蚁群算法提出了几种改进算法。
Ant colony optimization (ACO) is a new natural computation method from mimic the behaviors of ant colony. It is a very good combination optimization method. Ant colony optimization algorithm was recently proposed algorithm, it has strong robustness as well as good distributed calculative mechanism, and it is easy to combine with other methods, and the well performance has been shown on resolving the complex optimization problem. An ant colony optimization approach for the resource-constrained project scheduling problem (RCPSP) is presented. The TSP problem is chosen as example for introducing the basic principle of ACO, and several improvement algorithms are present for the problem of ACO.