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 group genetic algorithm 分组遗传算法(1)群体遗传算法(0)种群遗传算法(1)
 分组遗传算法
 We using a mathematics programming model represented the problem,then we designed the group genetic algorithm to solve the problem. 通过将组织设计过程中的决策者—资源分配问题抽象为数学规划问题,建立了解决鲁棒性决策者协调网络的模型,并为解决该类问题设计了分组遗传算法。 短句来源
 种群遗传算法
 In the algorithm, the globak convergent characteristic of the mugroup genetic algorithm is used to search for the possible extremums in the whole area,and the great feature of the QuasiNewton algorithm,which is descent in the direction of the grads of objective function,is used to search fast about the extremums. 此算法利用微种群遗传算法(μGA)的全局最优性在大范围内搜索可能的极值,而用拟牛顿(Quasi Newton)法的目标函数梯度下降特性在极值点附近快速搜索,从而实现了全局最优与快速搜索的有机结合。 短句来源
 “group genetic algorithm”译为未确定词的双语例句
 Thus, the better combination of global convergent and fast search is obtained,and then the optimizing effect of the hybrid algorithm is compared with that of the mugroup genetic algorithm after testing with several typical functions. 同时,通过几个典型的试验函数对此混合算法与微种群遗传算法的寻优效果做了比较。 短句来源 Aiming at the special problem of constrained optimization, multi-genus group genetic algorithm based on independence inches is presented. 针对带约束优化问题,提出了隔离小生境的多种群孤立进化遗传算法。 短句来源
 相似匹配句对
 group. 对照组给予胃乃安口服,每次 4 粒,每日 3 次。 短句来源 In group K. K. 短句来源 The genetic 用等电聚焦免疫固定技术调查成都地区汉族群体Bf的遗传多态性。 短句来源 The genetic relationship of these group was discussed. 推断AB组菌株可能是A组菌株向B组菌株进化的一个过渡类型。 短句来源 Features and Applications of Multi Group Genetic Algorithms 多重群体遗传算法的特点及应用 短句来源

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 The multi group genetic algorithms model was established and applied successfully in this paper.The new model accepted the concepts of the standard and independent gene/chromosome model,the multi group model consisting of the species group and the reproduction group,the accumulating way for establishing the initial species group.The model's working efficiency and adaptability to various kinds of problems are better obviously than that of the common model.The process of solving... The multi group genetic algorithms model was established and applied successfully in this paper.The new model accepted the concepts of the standard and independent gene/chromosome model,the multi group model consisting of the species group and the reproduction group,the accumulating way for establishing the initial species group.The model's working efficiency and adaptability to various kinds of problems are better obviously than that of the common model.The process of solving an optimization problem with the multi group genetic algorithms model consists of the establishment of the initial species group,the adaptation and evolution,the disposal after the evolution's mature and so on. Determining the value of the operators and getting multi peak optimization result were also discussed in this paper. 建立了多重群体遗传算法模型并成功地用于实际研究工作。多重群体遗传算法采用了标准化的独立的基因／染色体模型及由种群和繁殖群体组成的多重群体模型，并采用了积累方式建立初始种群，求解效率和对不同类型问题的适用性有明显的改善和提高。多重群体遗传算法模型求解优化问题的基本过程分为建立初始种群、适应与进化、进化成熟后的处理等内容。文章还讨论了遗传算子的确定和多峰值优化解集的获取等问题 Graph coloring is a NP Complete problem.By the analyzing some properties of proper k vertex coloring,k edge coloring,and total coloring of a graph,a new algorithm on proper k vertex coloring,k edge coloring,and total coloring of a graph based on group genetic algorithm and heuristics search is given.Experiments show that this new algorithm can obtain solutions of excellent quality. 图的着色算法是一种典型的NP 完全问题 在系统地讨论了图的正常顶点着色、边着色以及全着色的有关理论的基础上 ,提出了基于分组遗传算法和启发式搜索的图的正常 k 点着色 ,正常k 边着色以及正常k 全着色的新型混合算法 ,提出了评价算法性能的标准 实验仿真结果表明 ,新型混合算法可以获得问题高质量的解 ,即对图进行着色所使用的颜色数接近图的色数 A new algorithm is introduced for optimizing.In the algorithm, the globak convergent characteristic of the mugroup genetic algorithm is used to search for the possible extremums in the whole area,and the great feature of the QuasiNewton algorithm,which is descent in the direction of the grads of objective function,is used to search fast about the extremums. Thus, the better combination of global convergent and fast search is obtained,and then the optimizing effect of the hybrid algorithm... A new algorithm is introduced for optimizing.In the algorithm, the globak convergent characteristic of the mugroup genetic algorithm is used to search for the possible extremums in the whole area,and the great feature of the QuasiNewton algorithm,which is descent in the direction of the grads of objective function,is used to search fast about the extremums. Thus, the better combination of global convergent and fast search is obtained,and then the optimizing effect of the hybrid algorithm is compared with that of the mugroup genetic algorithm after testing with several typical functions. 提出了一种新型的优化算法。此算法利用微种群遗传算法(μGA)的全局最优性在大范围内搜索可能的极值,而用拟牛顿(Quasi Newton)法的目标函数梯度下降特性在极值点附近快速搜索,从而实现了全局最优与快速搜索的有机结合。同时,通过几个典型的试验函数对此混合算法与微种群遗传算法的寻优效果做了比较。 << 更多相关文摘
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