同时，局部搜索和变异操作受决策概率控制。
Moreover, the local search and mutation were controlled by decision probability.
该算法采用新的启发式变异算子和局部搜索算子。
Heuristics mutation operator and local search scheme are designed in the algorithm.
查询器的特性包括两个大的方面：寻路和局部搜索。
Query features fall into two general categories: Pathfinding and local search.
这种方法利用动态环境中物体的运动信息进行局部搜索。
This method makes use of the object movement information in the dynamic environment so that it makes the local searching procedure very efficient.
逐块搜索算法在基于关键块的局部搜索方法基础上进行改进。
Block-by-block searching algorithm was improved on the basis of local search algorithm that based on critical block.
采用与问题紧密相关的局部更新、全局更新和局部搜索机制。
The local update, global update and local search mechanism which closely related with the problem is given.
由于应用了自适应搜索技术，局部搜索能够快速找到局部极值。
The adaptive search technique enables local search to head for local extrema quickly.
并采用记忆单元机制，增强了算法局部搜索的能力，提高了其计算速度；
The memory unit mechanism is proposed to strengthen the local search ability of the algorithm and its calculation speed has been improved.
传统的求解方法包括动态规划法、贪婪算法、局部搜索法和分支定界法等。
Traditional methods include Dynamic Programming, Greedy Algorithms, Local Search Heuristics and Branch and Bound algorithms.
许多仿真和应用结果表明遗传算法具有计算时间长、局部搜索能力弱等缺点。
Though genetic algorithms (ga's) are regarded as highly efficient global search algorithms, they turned out in many applications and simulation calculations to be not good at local search.
算法局部搜索过程中采用的基于关键路径的邻域结构缩小了问题的搜索空间。
The critical block based neighborhood structure of the problem in the local search procedure reduces the searching space of the problem and increases the probability of ants finding good solutions.
该方法不仅简便、易行，而且具有很强的全局和局部搜索能力，加速效果明显。
This method not only have simple?easy speciality, but also have evident accelerating effect.
该算法充分利用基于概率的遗传算子的全局搜索能力和新算子较强的局部搜索能力。
The new GA takes the advantages of the global searching of genetic operators based on probabilities and the advantages of the local searching of the new operators.
通过柯西变异，提高算法的全局搜索能力，通过高斯变异，提高算法的局部搜索能力。
The algorithm's global searching ability is improved through Cauchy variation, and local searching ability is improved by Gauss variation.
提出三种有效的快速算法——局部搜索、多空间搜索和全局搜索来解决NP难度问题。
In this paper we propose there efficient arithmetic-weal search, much space search and overall situation search for sowing NP-hard problem.
该算法利用QAP现有算法得到初始解，然后利用局部搜索策略完成解的可行化和优化。
The GFO employs existing algorithms for the QAP to obtain an initial solution, then applies local search to gain feasibility and optimization.
该算法利用问题的邻域知识指导局部搜索，可克服元启发式算法随机性引起的盲目搜索。
The proposed algorithm utilizes neighborhood knowledge to direct its local search procedure which can overcome the blindness or randomness introduced by meta-heuristics.
针对对算法效率有极大影响的局部搜索，设计了一种名为逐块搜索算法的局部搜索方法。
As for local search which influenced the effectiveness of the algorithm seriously, a local search method named block-by-block searching algorithm was designed.
该模型采用GA对神经网络的初始权值和阈值进行优化，以避免可能的局部搜索最小现象。
With this model, the initial weights and threshold values of the neural network are optimized using GA to avoid the possibility of local search minimum.
对分布机制的研究表明，SGC有利于大范围搜索和脱离极小区域，而SGG较适合于局部搜索。
The distribution mechanism was analyzed, and it has been found that SGC is good at search in solution spaces while SGG is better at search in small local neighborhoods.
采用最优保存策略和高斯变异算子，保证算法的稳定收敛和提高算法在每个峰值附近的局部搜索能力。
The Elitist model is utilized to ensure the stable convergence, and the Gaussian mutation operator is used to enhance the local search ability around every peak value.
在逆序算子和对偶算子的性能研究基础之上，设计了逆序与对偶组合遗传算子，增强了局部搜索性能。
Inverse and dual combination operator is defined as a new genetic operator based on respective application study of inverse operator and dual operator, which can improve local searching.
CLARANS算法是经典的划分聚类算法，其核心思想是采用随机重启的局部搜索方式搜索中心点。
As a classical partition clustering algorithm, CLARANS USES local search with random restart to find clusters central points.
CLARANS算法是经典的划分聚类算法，其核心思想是采用随机重启的局部搜索方式搜索中心点。
As a classical partition clustering algorithm, CLARANS USES local search with random restart to find clusters central points.
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