1) Ant Colony Optimization (ACO)
蚁群最优
1.
Tabu Search (TS) behaves well in finding global optimum of combined optimization problems, whereas its local search is not satisfactory due to diversity; Ant Colony Optimization (ACO) behaves well in finding local optimum, whereas its global search depends on selection of the evaporation coefficient.
禁忌搜索(TS)算法具有强大的全局优化性能,但其局部搜索性能易受分散性的影响;蚁群最优(ACO)算法的正反馈机制使其具有强大的局部搜索性能,但其全局优化性能的优劣在很大程度上与蒸发系数的选择有关,如选择得不合适易使算法陷于局部最优。
2.
In this paper, a novel method called Ant Colony Optimization (ACO) is presented to solve the problem of transmission network expansion planning.
文章提出了一种基于蚁群最优的输电网络扩展规划法(ACO)。
2) ACO(ant colony optimization)
蚁群最优化
3) Ant Colony 0palmization (ACO)
蚁群最优算法
4) ant colony optimization
蚁群优化
1.
Routing-planning of city logistics distribution based on higher-lower level ant colony optimization algorithm;
基于双层蚁群优化算法的城市物流配送路径规划
2.
Recent progress of ant colony optimization and its applications;
蚁群优化的研究进展及应用
3.
Study of continuous ant colony optimization algorithm;
连续蚁群优化算法的研究
5) ACO
蚁群优化
1.
ACO Scheduling Approach for Manufacturing Cells Based on Flexible ProcessLeng Sheng,Wei Xiaobin,Wang Ningsheng;
柔性工艺路线蚁群优化单元作业调度
2.
A New Algorithm Based ACO for Routing Problem in Application-Layer Multicast Network;
基于蚁群优化的应用层多播路由算法
3.
The parallelism of ant col-ony optimization(ACO) is feasible in UCAV path planning under complicated combat environments,but the basic ACO algorithm has the limitation of stagnation,and is easy to fall into local optimum trouble.
蚁群优化(ACO)算法的并行实现机制适合于复杂作战环境下的UCAV航路规划,但是基本ACO算法有易陷于局部最优解的缺点。
6) ant colony optimization(ACO)
蚁群优化
1.
In order to obtain an optimal performance,ant colony optimization(ACO) method was used to optimize the parameter of the controller.
针对使用传统PID参数整定方法难以获得最优性能的问题,介绍了一种基于内模控制的PID控制器设计方法,使用蚁群优化方法对其中的参数进行优化,使系统达到某一最优性能指标。
2.
The proposed algorithm is based on ant colony optimization(ACO) to allocate valuable resources(i.
对此该文在CDMA2000下行链路MAC层进行了探讨,提出了一种基于蚁群优化算法的方案,对突发的高速数据请求分配系统资源(即:信道)。
3.
Aiming at the characteristics of dynamic Bayesian transition networks, this paper proposes a structure learning algorithm based on Ant Colony Optimization(ACO) named ACO-DBN-2S by extending the static Bayesian networks structure leaning algorithm I-ACO-B.
针对动态贝叶斯转移网络的特点,以I-ACO-B为基础,提出基于蚁群优化的分步构建转移网络的结构学习算法ACO-DBN-2S。
补充资料：群蚁溃堤
1.喻小患酿成大祸。语本《韩非子．喻老》:"千丈之堤，以蝼蚁之穴溃;百尺之室，以突隙之烟(熛)焚。"
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条