1) multi-population
多种群
1.
A multi-population differential evolution algorithm and its application in flexible job shop scheduling;
多种群差分进化算法及在柔性车间作业调度中的应用
2.
Task scheduling algorithm based on multi-population and level set;
基于多种群及水平集的任务调度算法
3.
Multi-population Evolution Strategies for Multi-modal Function Optimization;
多模态函数优化的多种群进化策略
2) multigroup
多种群
1.
To improve the performance of genetic algorithm,greedy algorithm which has more local search ability is imported to genetic algorithm and is well combined with the ideas of simulated annealing and multigroup parallel evolution in this paper.
为了提高遗传算法的性能,论文通过将局部搜索能力较强的贪婪算法引入遗传算法,并且同模拟退火和多种群并行遗传进化思想有机结合起来的方法,提出了一个改进型的算法——多种群退火贪婪混合遗传算法(MultigroupAnnealingGreedyHybridGeneticAlgorithm,简称MAGHGA)。
2.
A parallel version of PSO based on multigroup and migration is proposed.
文章先简要介绍了粒子群算法的标准版本,对比细粒度的粒子群算法的简单并行,引入种群和移民的思想,提出了一种基于多种群的粒子群算法的并行版本。
3.
Then a multigroup parallel genetic algorithm(GA) is used to solve the optimization problem.
针对有色冶金企业原料库存的实际情况 ,建立了一个以资金损耗最小为直接性能指标的原料库存优化模型 ,并提出了一种多种群并行遗传算法对该模型进行优化。
3) multiple populations
多种群
1.
Multiple Populations Coevolution and the Application in the Generative Conception Design;
多种群协同进化及其在创新概念设计中的应用
2.
Firstly,this paper put forward new Richards model of multiple populations based on growth model of single population,then gave the biological meaning of related parameters and thought that this model included all relationships effectively among populations (competition,partial-advantage,partial-deleteriousness,mutualism,community,etc).
在单种群生长模型的基础上提出了多种群下的Richards模型,并对相关的参数给出了明确的生物学意义,认为该模型有效地包括了种群的竞争关系,偏利与偏害关系,共生与互惠关系等。
4) population diversity
种群多样性
1.
Genetic algorithm based on instructing by population diversity;
基于种群多样性指导的遗传算法
2.
To overcome premature searching by standard particle swarm optimization(PSO)algorithm for the great loss of population diversity,a novel adaptive PSO is proposed,which can dynamically change inertia weight coefficients by the measure of population diversity.
针对标准粒子群算法在进化过程中种群多样性降低而早熟的问题,提出了一种根据种群多样性测度动态改变惯性权重系数的自适应粒子群算法,该算法能够平衡算法的全局探索和局部开发能力,不仅有效地避免早熟,而且具有较快的收敛速度。
3.
Focusing on the problems existed in some adaptive genetic algorithms that cannot take acc ount of population features and are difficult to converge to optimal solution s tead ily, the reasons of stopping evolution or degeneration are analyzed in view of f itness average and population diversity.
针对现有自适应遗传算法无法兼顾群体特性 ,难以稳定地收敛到最优解的问题 ,从种群多样性和适应度均值变化的角度 ,分析了进化停滞或退化的原因 。
5) diversity of population
种群多样性
1.
Based on the variance of fitness value, an index that can reflect the diversity of population in genetic algorithm is defined.
根据适应度的方差,定义了一种度量种群多样性的指标。
2.
A new index which can reflect the diversity of population in genetic algorithms, is defined in this paper and used to adjust the probabilities of crossover and mutation.
提出了一种度量种群多样性的新指标 ,将其应用于交叉概率和变异概率两个参数的自适应调整 ,再将自适应的思想和并行计算的思想结合起来 ,提出了一种在个人计算机上实现的改进自适应遗传算法 -自适应伪并行遗传算法(APPGA) 。
3.
We designed a migration operator and crossover operator based on diversity of population functions,and made dynamic adjustments on crossover and mutation probabilities.
为了改善遗传算法的收敛性能,提出了一种基于个体适应度的种群多样性度量函数,恰当地反映了遗传算法的进化阶段,预报了早熟收敛的趋势。
6) poly-population algorithm
多种群算法
补充资料：种群增长率(见种群出生率)
种群增长率(见种群出生率)
种群增长率见种群出生率。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条