1.but as a good optimization method , the researches on using tabu search as the learning algorithms for fuzzy neural networks are very few.
然而，目前使用禁忌搜索算法作为模糊神经网络参数学习算法的研究却不多见。
2.In addition, the effectiveness of the mixed tabu search algorithm is proved by means of theoretical analysis and simulation examples.
并通过理论分析和仿真算例，证明了该混合禁忌搜索算法的有效性。
3.The optimization quality and computation time of set covering arid tabu search algorithms were analyzed and compared.
分析和比较了集合覆盖和禁忌搜索两种高效布局算法的优化性能和计算时间。
4.Then, the transformation method from multi-objective to single-objective is given and the tabu search algorithm is used for simulation.
然后提出了将多目标转化为单目标的方法，并利用禁忌搜索算法对该问题进行仿真。
5.Linear programming and tabu heuristics are considered the best available heuristic routing algorithm.
线性规划和tabu启发法被认为最佳的可利用的启发式发送算法。
6.A genetic-tabu algorithm (GATS) was given for topology optimization of truss structures subject to multiple loading cases and constrains.
采用遗传禁忌搜索算法求解多工况多约束的桁架结构拓扑优化问题。
7.A hybrid particle swarm and tabu search optimization algorithm with fuzzy technology was presented to solve the optimization model.
在求解模型时采用模糊化处理技术，并提出了综合禁忌搜索思想的改进粒子群算法。
8.These cumber the problem's solving badly. Genetic-Tabu hybrid meta-heuristic algorithm constructed in this paper is a double-deck structure.
本文构造的遗传禁忌混合算法是一个两层的搜索结构，充分利用了不同领域的搜索方法。
9.Experimental results show that the parallel tabu search algorithm has better performance.
实验结果表明该并行禁忌搜索算法性能较高。
10.Experimental results show that CTS improves the performance of the traditional tabu search.
实验结果表明CTS的性能要优于传统的禁忌算法。