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。
Ant Colony algorithm is a novel simulated evolvement algorithm solving complicated combinatorial optimization problem and its typical feature is swarm intelligence.
本文讨论了群集智能的两种算法，蚁群智能与微粒群智能。
In this paper, we review ant colony algorithm and particle swarm optimization.
蚁群算法是受自然界蚂蚁觅食过程中，基于信息素的最短路径搜索食物行为启发，提出的一种智能优化算法。
Ant Colony Algorithm (ACA) is an intelligence-optimized algorithm coming from the illumination of food-seeking behavior by ants based on the shortest route of daumone.
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。
The basic and typical algorithm of swarm intelligence is particle swarm optimization and Ant colony oprimation.
研究了混合型装配线平衡问题的智能蚁群优化算法。
Ant colony optimization for mixed-model assembly line balancing problem (MMALBP) is studied.
仿真结果表明蚁群算法与模糊控制相结合的智能控制技术，更有效地降低通行车辆在交叉口的平均延误时间，更能适应复杂多变的交通环境。
The results indicates the algorithm can effectively reduce the average delay time of vehicles in the intersection, Correspondingly enhance the passing capacity of the intersection.
蚁群算法是一种新型的用于求解组合优化或函数优化问题的智能优化算法。
Ant colony algorithm is a new intelligent optimization algorithm for solving combinatorial optimization problem or function optimization problem.
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 swarm intelligence heuristic approach that inspired from ants finding foods.
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.
蚁群算法是一种基于群体智能的算法，蚂蚁群体智能有广泛的实际应用，该智能有其本身的优点，但同时也存在群体迷失的问题。
The swarm intelligence of ants has advantages in itself, while it can easily bring about the problems of swarm lost.
分析了将智能算法应用到信号设计中的可行性，并将蚁群算法运用到正交多相编码信号的设计中，对设计的多相码进行了分析研究。
Analyze the feasibility of applying intelligent algorithms to the signal design and design orthogonal polyphase coded signals using the ant colony algorithm.
蚁群算法是一种新兴的群智能算法。
Ant Colony Optimization (ACO) algorithm is a new swarm intelligence heuristic algorithm.
采用蚁群智能算法解决路径寻优问题。
The ant colony algorithm was adopted to solve the intelligent optimization path problems.
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。
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.
因此，实现基于蚁群算法的综合布线系统，有着重要的意义，也进一步提高了智能建筑的智能化程度。
Therefore, based on the ant colony algorithm to achieve the integrated wiring system is of important significance, but also further enhance the level of intelligent building intelligent.
作为计算智能和群智能的重要分支之一，蚁群优化算法已经成功地应用于许多组合优化问题的求解。
As an important branch of computational intelligence and swarm intelligence, ACO have been successfully applied to solve many combinational optimization problems.
作为计算智能和群智能的重要分支之一，蚁群优化算法已经成功地应用于许多组合优化问题的求解。
As an important branch of computational intelligence and swarm intelligence, ACO have been successfully applied to solve many combinational optimization problems.
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