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1)  Simplification of ant colony optimization
蚁群优化的简化
2)  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
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3)  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。
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4)  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。
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5)  ant-colony optimization
蚁群优化
1.
Moreover,based on the traditional ant-based algorithm,we propose an ant-colony optimization based service aware routing(ASAR).
进而,利用改进的蚁群算法,设计了一个基于蚁群优化的服务感知路由算法ASAR(Ant-colony optimization based Service Aware Routing)。
2.
An Ad Hoc load-balancing routing algorithm based on Ant-Colony Optimization(ALRBA) is proposed.
为了充分利用 Ad Hoc 网络资源,降低拥塞程度,提出了一种基于蚁群优化的 Ad Hoc 负载均衡路由算法(ALRBA),算法具有良好的分布式特性,能为网络提供大量的冗余路径,增强了网络的抗毁性。
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6)  ACO(ant colony optimization)
蚁群最优化
补充资料：蚍蚁
1.唐韩愈《<张中丞传>后序》:"外无蚍蜉蚁子之援。"后因以"蚍蚁"比喻微小的力量。
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