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 system combined the Ant Colony Optimization (ACO) algorithm and the dispatching priority heuristic algorithm to solve the scheduling problems existing in mold parts with work piece restrictions.

该系统利用蚁群算法和优先分配启发式算法相结合的调度算法，解决具有工件约束的模具零件的调度问题。

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。

Realize DN - ACO target tracking algorithm in simulation platform and verify the energy efficiency of the algorithm.

在该仿真平台上实现了DN -ACO 目标跟踪算法,并验证算法的能量有效性.

Acetoin was shown to function as an inducer for the expression of aco genes, whereas glucose exhibited a repression effect.

被认定为诱导物的乙醯甲基甲醇可刺激启动区的表现，而葡萄糖则表现抑制现象。

The algorithm used serial schedule generation scheme(SSGS) to generate a feasible schedule and employed ACO to search the optimal schedule.

该方法采用串行进度产生方案（SSGS）产生可行进度，并利用ACO进行最优进度的搜索。

The algorithm used serial schedule generation scheme (SSGS) to generate a feasible schedule and employed ACO to search the optimal schedule.

该方法采用串行进度产生方案（SSGS）产生可行进度，并利用ACO进行最优进度的搜索。

Combining with the modified adaptive weight approach (MAWA), the ACO algorithm can find out the optimal solution, and define the Pareto front as well.

通过与改进自适应权重方法（MAWA）的结合，ACO算法不仅可以找到最优解，还可以得到问题的帕雷托前沿。

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。