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Local optimum is not even an indication for the global optima. 局部利益与整体的利益并不一致。
The approach has also been advanced to speed convergence and avid local optimum. 该方案能够快速正确地实现分割，且不需事先认为的确定分割类数。
Compared with TGA, the results show that ICSA has better capability in avoiding getting into local optimum and astringency. 3. 仿真结果表明，TGA和ICSA都可以有效的解决一定规模下的TSP问题，并且ICSA具有更高的收敛性，不易陷入局部最优。
As a new optimization technique, chaos bears randomicity, ergodicity and the superiority of escaping from a local optimum. 摘要混沌是一种新颖的优化技术，具有随机性、遍历性的特点和易跳出局部极值的能力。
In order to solve the problem of genetic algorithm in local optimum easily，this paper increases a tabu search in a mutation method. 为解决遗传算法易陷入局部最优的问题，提出了一种在变异算子中增加禁忌表的方法。
The ergodicity of chaotic optimization can avoid it from dropping into local optimum easily;the randomicity and the order of it can provide plenty of temporal and spatial dynamic. 混沌优化的遍历性可作为搜索过程中避免陷入局部极小值的一种优化机制，随机性和规律性使它具有丰富的时空动态。
When the optimum information of the swarm is stagnant, some particles in the population are initialized again to reduce the possibility of trapping in local optimum. 为减小陷入局优的可能性，当群体最优信息陷入停滞时，对群体进行部分初始化来保持群体的活性，并讨论了改进算法的适用范围。
Because of GA s global optimum ability, using GA for codebook training can obstain a global optimum codebook, and overcome local optimum limitation of traditional algorithms. 遗传算法有卓越的全局优化搜索能力,易搜索到全局最优的矢量分类,形成高度优化的码书,可克服传统方法局部优化的缺陷。
The mutated individual follows the advantage direction of current population, so it can jump local optimum and get the global optimum and it can avoid the semi-blind of conventional Darwinian-type evolutionary computation. 这样，在利用优势个体确定变异方向的同时，借助劣势个体来搜索潜在的优势个体，使得个体变异既能沿着当前种群的优势方向前进，又能跳出局部最优，寻求全局最优，从而成功地克服传统达尔文演化策略的半盲目性。
By using the multi-parent crossover operator and the new mutation operator, the variety of population and the ability of MPGA algorithm breaking away from the local optimum are effectively improved. 该算法通过引入多父体杂交算子和新的变异算子，有效的增强了种群的多样性及算法跳出局部最优解的能力。
This algorithm uses the strategy of adjusting pheromone on best path and restarting algorithm，and can solve the problem that ant algorithm is easy to fall into local optimum solution. 算法采用调整最优解路径上的信息素和算法重启策略，较好地解决了蚁群算法易于陷入局部最优的问题。
In the optimization engine, genetic algorithm is adopted to avoid local optima. 在优化引擎中使用了遗传算法用来避免局部的优化解。
Moreover, we improve the mutation to avoid the remaining local optima of GAs. 为了避免陷入局部最优，对变异算子进行了改进。
But along with the extending of the problem, GA tends to get local optimums. 但是随着问题规模扩大，简单遗传算法容易出现“早熟”或陷入局部极值。
The basic principle of CPSO algorithm is that chaos initialization is adopted to improve individual quality and chaos perturbation is utilized to avoid the search being trapped in local optimum. 该算法的思想是采用混沌初始化进行改善个体质量和利用混沌扰动避免搜索过程陷入局部极值。
At last, the optimum in all the local optimums is selected as the global optimum. 最终选择所有局部最优解当中最优的个体作为全局最优解。
Ant Colony Optimization algorithm(ACO)has the limitations of poor convergence, and is easy to fall in local optima. 针对蚁群优化算法(Ant Colony Optimization; ACO)收敛速度慢、易陷于局部最优解的缺点;提出了一种基于协同进化思想的蚁群算法;用于求解TSP问题.
For multimode function optimization, a quantum SPSO (Q-SPSO) is provided to deal with multiple local optima. 实验分析了采样周期对算法优化行为的影响。
Simulated annealing tends to be trapped in local optima, but it also possess powerful fine adjustment ability. 模拟退火算法容易陷入局部最优解,但是具有很强的微调能力。
The heuristic approach can be an alternative to solve the model above with simplicity and immune to the local optima. 采用启发式算法求解简单易行，最优解具有全局性，且与初始点选择无关。