针对基本蚁群算法中存在的早熟现象，提出了基于证据理论的搜索方法。
An effective method based on the theory of evidence is put forth to improve the searching performance of basic ant colony algorithms.
该方法克服了基本蚁群算法的不足，能够满意地实现PID控制参数优化。
This method not only overcomes the shortage of basic ant colony algorithm, but also perfectly realizes the optimization of PID control parameter.
从随机优化技术出发，针对基本蚁群算法，提出了一种随机摄动蚁群优化算法。
A novel ant colony optimization algorithm with random perturbation behavior (RPACO) based on combination of general ant colony optimization and stochastic mechanism is developed in this paper.
然而，基本蚁群算法在求解组合优化问题过程中容易出现过早收敛或停滞现象。
However, the traditional algorithms have the problems of early convergence or stagnation in the process of combinatorial optimization problems.
实验结果表明：新提出的算法明显快于基本蚁群算法，佳点集杂交算子对解的优化有较好的作用。
Experiment shows that new algorithm is obviously fast than basic ant algorithm, and good point crossover operator is benefit to optimization of solution.
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.
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.
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.
分别用递推最小二乘算法、基本蚁群算法与混合蚁群算法训练模糊系统，混合蚁群算法的收敛效果优于递推最小二乘算法与基本蚁群算法。
The convergence error of hybrid ant colony algorithm is small in comparison to that of recursive least square algorithm and basic ant colony algorithm.
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.
然后在簇结构和簇内两个层次上分别运用蚁群算法，生成以簇为基本需求点的行车路线和簇内点集的行车路线，最后获得最佳路径表。
Then applying Ant colony algorithm to two-layer structure for generating clusters rout plan and nodes rout plan. At last, get the optimal rout table.
将蚁群算法的基本原理用到物流配送网最短路径搜索中，对降低配送成本有重要意义。
The basic theory of ant colony algorithm is applied to shortest path search in the logistics network of distribution for reducing the cost of logistic distribution.
针对移动自组织网络资源受限的特点和目前已有的蚁群路由算法比较复杂的问题，提出一种基本蚁群路由算法。
Concerning that the resource in mobile Ad Hoc network is limited and the existing ant routing algorithms are complex, a basic ant routing algorithm was proposed.
发现基本蚁群优化算法存在慢收敛且易停滞等问题。
The ant colony optimization algorithm has found slow convergence and easy to stagnation.
发现基本蚁群优化算法存在慢收敛且易停滞等问题。
The ant colony optimization algorithm has found slow convergence and easy to stagnation.
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