Ant Colony algorithm is a novel simulated evolvement algorithm solving complicated combinatorial optimization problem and its typical feature is swarm intelligence.
蚁群算法是一种新颖的求解复杂组合优化问题的模拟进化算法，它具有典型的群体智能的特性。
This paper provides a model of the clustering and an optimized ant colony-clustering algorithm which is based on the swarm intelligence and that mathematic model is provided at the same time.
该文通过对现有群体智能理论和聚类算法的研究，提出了一种基于群体智能理论的聚类模型，并在此基础上给出了一种优化蚁群聚类算法。
The basic and typical algorithm of swarm intelligence is particle swarm optimization and Ant colony oprimation.
目前，群智能理论研究领域有两种主要的算法：微粒群优化算法和蚁群优化算法。
Ant Colony Optimization (ACO) algorithm is a new swarm intelligence heuristic algorithm.
蚁群算法是一种新兴的群智能算法。
Ant colony algorithm is a kind of swarm intelligence heuristic approach that inspired from ants finding foods.
蚁群算法是一种群体智能搜索算法，它来源于蚂蚁寻食的启迪。
Ant Colony algorithm is a kind of algorithm that simulates swarm intelligence. It has a good performance in solving the problems based on Discrete Space.
蚁群算法是一种模拟群体智能的算法，在解决基于离散空间的问题时表现出良好的性能。
The swarm intelligence optimization algorithm include: ant colony optimization algorithm, particle swarm optimization algorithm, artificial bee colony algorithm and artificial fish swarm algorithm.
目前提出的群智能优化算法有蚁群优化算法、粒子群优化算法、人工鱼群算法、人工蜂群算法。
The swarm intelligence optimization algorithm include: ant colony optimization algorithm, particle swarm optimization algorithm, artificial bee colony algorithm and artificial fish swarm algorithm.
目前提出的群智能优化算法有蚁群优化算法、粒子群优化算法、人工鱼群算法、人工蜂群算法。
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