Using access-control lists (ACLs), you could have created an action in the products controller and used it to grant create access to the user's access-request object (ARO) on each dealer ACO.
您可以使用访问控制列表(Access Control List,ACL)在products控制器中创建一个操作，并使用它为每个经销商aco上的用户访问请求对象(ARO)授权create访问权限。
This paper presents a new improved ACO.
为此，该文提出了一种新的改进蚁群算法。
Ant Colony Optimization (ACO) algorithm is a new swarm intelligence heuristic algorithm.
蚁群算法是一种新兴的群智能算法。
In this paper, ant colony algorithm (ACO) was applied to solve the prioritizing problem of flight landing.
本文将蚁群算法用于着陆航班的排序问题。
The theory part of ACO focuses on establishing the computation model of ACO, analyzing the convergence of ACO, etc.
理论方面主要研究算法的模型，分析其收敛性和收敛速度以及控制参数对算法性能的影响等。
So it is necessary to improve the current ACO algorithms, which would have better performance for solving large TSP.
因此，有必要对算法进行改进，使算法在中大规模的TSP问题上有较好的性能。
ACO adopts parallel computation mechanism, has strong robustness and is easy to combine with other methods in optimization.
蚁群算法采用分布式并行计算机制，易与其他方法结合，具有较强的鲁棒性等特点。
Compared with the theory aspect of ACO, the application aspect of ACO extends to rather wide fields and makes great success.
相对于理论部分，对蚁群算法的应用部分的研究则开辟了相当广阔的领域，也取得了很大的成功。
The dynamic combination of GA and ACO in the strategy is realized by the difference of population similarity in different iterations.
该策略通过不同迭代次数中种群相似度的差值实现两种算法的动态融合。
But compare to other bionics evolution algorithms ACO has disadvantages such as long-time searching and local best solution and so on.
但是与其它仿生学进化算法相比，蚁群算法存在搜索时间长、易陷入局部最优等缺点。
In order to improve the performance of ACO algorithm, an ACO algorithm with the dynamic parameter decision model was presented in this paper.
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 this study, using chewing cane as experimental materials, cloned ACO gene by homology cloning techniques and made some other researches on it.
本研究以果蔗为实验材料，利用同源克隆技术克隆了ACO基因，并对该基因做了相关研究。
ACO algorithm is basically a multi agent system where low level interactions between single agents result in a complex behavior of the whole ant colony.
ACO算法本质上是一个多代理系统，在这个系统中单个代理之间的交互导致了整个蚁群的复杂行为。
This dissertation defines the heuristic information in ACO properly and designs the corresponding ACO's state transition rule and pheromone updating rule.
论文同时对蚁群优化中的启发式信息给出了合理定义，并设计了相应的状态转移规则和信息素更新规则；
Experimental results show that the novel algorithm can get a better solution, and convergence rate is enhanced with a comparison to the I-ACO-B algorithm.
实验结果表明，与I-ACO-B算法相比，该算法不仅能获得更好的解，且收敛速度也有一定的提高。
The applications of ACO to static and dynamic COPs, such as traveling salesman problem, quadratic assignment problem, network routing problem are reviewed.
结合旅行商问题、二次指派问题以及网络路由问题等典型组合优化问题，概述了ACO在静态组合最优化和动态组合优化问题中的应用。
Relative to the ACO algorithm, GPSO algorithm is better than the ACO algorithm whether in the search speed, search precision, or in the algorithm running time.
相对于蚁群算法来说，不论是在搜索速度、搜索精度，还是在算法的运行时间上，GPSO算法都要优于蚁群算法。
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。
By analyzing the function and significance of parameters, the parameter setting of ACO algorithm can be described as a multifactor and multilevel optimization problem.
通过对蚁群优化算法各操作参数作用与意义的分析，将蚁群优化算法的参数设定描述为一个多因素多水平优化设计问题。
Global path planning problem for autonomous underwater vehicle (AUV) based on large-scale chart data is investigated by using ant colony optimization (in shorts, ACO) algorithm.
在大范围海洋环境中，应用蚁群算法对自主式水下潜器(AUV)的全局路径规划问题进行了研究。
On the algorithm solving model, this paper introduces ACO algorithm, and makes a comparison between the ACO algorithm and other optimization algorithm, then points out its advantages.
对于其模型的求解算法，文章引入了蚁群算法，并将蚁群算法与其它优化算法做了比较，说明其优点所在。
Ant Colony optimization (ACO) is a new-style simulating evolution algorithm. The behavior of real ant colonies foraging for food is simulated and used for solving optimization problems.
蚁群算法是一种新型的模拟进化算法，它通过模拟蚁群在觅食过程中寻找最短路径的方法来求解优化问题。
Shanghai ACO Chemical Co. Ltd. was founded in 1996. With special approval by the relative authorities of China, it is a high-tech enterprise which offers varieties of chemical products.
上海亚科化工有限公司创始于1996年，是一家经国家相关部门批准、专业提供各种化学工业产品及机电设备的高新技术企业。
After lots of experiments ACO has exhibited its excellent performance and efficiency in experiments for solving a great lot of combinatorial optimization problems, and now it is used in many areas.
大量实验结果表明，它在解决许多组合优化问题时都能表现出较好的求解能力，目前此算法已经得到了比较广泛的应用。
After lots of experiments ACO has exhibited its excellent performance and efficiency in experiments for solving a great lot of combinatorial optimization problems, and now it is used in many areas.
大量实验结果表明，它在解决许多组合优化问题时都能表现出较好的求解能力，目前此算法已经得到了比较广泛的应用。
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