提出一种改进的蚁群算法，并将其与启发式方法相结合以解决多点路由问题。
In this paper, the performance of as is improved and the improved as is combined with the heuristic algorithm to solve the multicast routing problem.
进一步采用改进的蚁群算法来对发酵过程的控制变量进行优化，使发酵的产物产量得到提高。
Based on the neural network models, the control variables are optimized with improved ant algorithm. And the yield of the product can be increased by optimization.
针对出租车路径规划问题的特点以及蚁群算法在这方面应用的一些不足，提出了一种改进的蚁群算法。
An improved ant colony algorithm was presented, which aimed at the character of the taxi routing problem and the drawback of ant colony system applied in the planning of the transportation resource.
仿真结果表明改进的蚁群算法能有效的寻找到一棵性能良好的组播树，并能够满足各种业务的服务质量需求。
The simulation results show the improved ant colony algorithm can effectively find a good performance multicast trees, and meet the business needs of the quality of service.
改进的蚁群算法对该模型进行优化计算，该船的中剖面纵向结构单位长度的重量减轻3.35%，结果表明蚁群算法是行之有效的。
It proved effective that the ant colony algorithm can improve the optimal design. As a result, the weight of the mid ship section structure in unit length may decrease by 3.35%.
基于这种情况提出了一种改进的蚁群算法，该算法采用基于组成员节点驱动的方式构造组播树，并在概率转移函数中添加了方向因子，使蚂蚁在寻找路径时摆脱了最初的盲目性，以更大的概率快速向源节点靠近。
This new algorithm adopts the group-mem-ber-node-driven method to create the tree and adds the orientation factor to the probability function, which enables the ant to get rid of the I.
证明了改进蚁群算法解决公交调度问题的高效性和较强的适用性。
It is proved that ACA is efficient and robust in solving transit scheduling problem.
在对洞庭湖的水质状态进行分析时，运用基于改进蚁群算法的投影寻踪评价模型对其2001年的水质状态进行评价。
We use the projection pursuit model based on the improved ant colony algorithm to analyze the status of the water quality of the Dongting Lake in 2001.
第三部分针对配电网无功电源规划的数学模型，应用改进蚁群算法进行求解。
In part three, the paper USES improved ant colony search algorithm to solve the problem of reactive power supply programming.
采用基于动态信息素更新策略的改进蚁群优化算法，在保证优化目标的基础上，迅速收敛并得到最优解，从而提高调度系统的可行性，增强系统稳定性。
Secondly, the algorithm based on the dynamic pheromone updating ensures the quick convergence and the optimal solution, thus improving the feasibility and the stability of the schedule system.
针对当前我国电力线通信的现状和特点，提出了一种能够实现远程抄表自动路由的改进蚁群搜索算法，给出了路由协议的基本框架，并建立了路由模型。
According to the actuality and characteristics of power line communication currently, an automatic routing method based on ant colony algorithm was presented, which could achieve remote meter reading.
在介绍蚁群算法基本原理以及探讨该算法的缺陷基础上，针对多处理器任务调度问题，提出了一种基于改进型蚁群算法的调度策略。
After the basic theory of ACA is introduced, a multiprocessors scheduling policy based on an improved ant colony algorithm is proposed in this paper.
对蚁群算法作了改进，思路是K-均值方法混合，利用K-均值方法的结果作为初值。
The algorithm is then extended to use K-means clustering to seed the initial solution and the information pheromone is adjusted according to them.
为此，该文提出了一种新的改进蚁群算法。
在基本蚁群算法的基础上，用确定性选择与随机性选择相结合的方法对节点的状态转移规则进行改进。
Grid method was applied to establish an environment model. The conversion rule of node state was improved by combining decided selection with random selection.
在原有标准蚁群算法的基础上采用了新的状态转移规则，讨论了各种不同的轨迹更新规则对仿真结果的影响，并通过统计数据验证了改进型蚁群算法优于标准的蚁群优化算法。
The novel transition rule and the different pheromone reinforcement rules are discussed in this paper when ant colony systems are applied to minimizing the make-span in job shop scheduling problem.
针对该算法易陷入局部最优解、求解速度较慢的缺陷，本文通过对蚁群算法的改进和调整，构造出最大—最小蚁群算法。
But the algorithm easily trapped into local optimal solution and solved the problem more slowly, this paper constructed Max-Min ACO algorithm through the improvement and adjustment of ACO algorithm.
将最短路径的信息反馈到系统中作为搜索的指导信号，并改进节点选择方法，以提高应用蚁群算法搜索无人机三维航路的效率。
To improve the efficiency of path planning, the message of the shortest path was introduced in the system as a searching guidance signal, and a modified nodes selection method was also given.
最后，本文实现了蚁群算法解决TSP问题和数据分类的原型系统，并以此为基础对改进算法进行了性能测试。
Finally, a prototype system to solve the TSP and data classification was developed, and accordingly the performance of improved algorithm was evaluated.
提出一种适用于钢坯修磨轨迹优化问题的改进蚁群算法，给出一种修磨轨迹优化问题的实用数学模型。
An improved Ant Colony Algorithm (ACA) is presented that can be used to search shortest grinding path for the grinding machine and the grinding path optimization mathematical model is given.
介绍了蚁群算法基本模型的原理、特点和实现方法，并介绍了目前针对基本蚁群算法不足所提出的改进措施。
Then the principle, the model, the characteristics and the management about the basic algorithm of ACO are also presented.
同时，还介绍了蚁群优化算法在交通模型中的应用，提出基于改进蚁群算法的增量交通分配模型。
At the same time, this paper also introduces ant colony algorithm application in transportation model, bring forward increment traffic assignment model based on improved ant colony algorithm.
该方法设定适应度函数阈值改进了蚁群算法的信息素更新机制；
The pheromone-updating mechanism is improved by threshold of the fitness function in presented method;
为使蚁群优化算法在应用中发挥最佳的寻优性能，提出带有动态参数决策模型的改进蚁群优化算法。
In order to improve the performance of ACO algorithm, an ACO algorithm with the dynamic parameter decision model was presented in this paper.
基于对蚂蚁种群中兵蚁和工蚁在觅食过程中合作关系的仿生，提出了一种改进型蚁群算法。
A novel ant colony algorithm is proposed based on the bionics of cooperation relation between soldier ant and worker ant in the foraging process.
针对基于网格的高性能计算平台的特点，作者将蚁群优化算法与网格调度技术相结合提出了一个改进算法。
Considering the characteristic of GHPCP, the author puts forward an improved algorithm by combining the ant optimization algorithm with grid scheduling.
实验结果证明：对基本蚁群算法的改进，提高了运算速度和鲁棒性，增强了蚁群算法在移动机器人路径规划中的适应能力。
The experiment results showed that improved algorithms 'operating speed and robustness is improved, adaptability of ant colony algorithms on mobile robot path planning is enhanced.
通过实验证明，改进后的并行蚁群算法程序执行时间明显缩短，执行效率显著提高。
The experiment proves that the improved method makes the time of program execution shorter significantly and the efficiency higher observably when solve large scale TSP.
通过实验证明，改进后的并行蚁群算法程序执行时间明显缩短，执行效率显著提高。
The experiment proves that the improved method makes the time of program execution shorter significantly and the efficiency higher observably when solve large scale TSP.
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