并行遗传算法 meaning in English
parallel genetic algorithm pga
parallelgeneticalgorithm,pga
pga
Examples
- Considering the electrovalence , the curve of water consumption and the reliability of water supply , this paper respectively sets up the model based on the maximal flux and the model based on the expectation flux . it takes yearly expenditure converting value and yearly cistern converting value as target function and takes continuity equation , velocity of flow and compression resistance of cast iron pipeline as restrictions and sets up the pga model on optimal design of water supply networks
考虑到峰谷电价、用水量变化曲线及用水可靠性因素的影响，分别建立了以最高时流量设计管网的模型和以期望时流量设计管网的模型，以年费用折算值加上清水池年造价折算值为目标函数，以连续性方程、管中流速和铸铁管耐压值等为约束条件，进行并行遗传算法对给水管网优化设计的实现。 - For standard genetic algorithm has the defects of slowly converging and easily falling into local extremum ， the author designed and realized the adaptive multi - population parallel genetic algorithm ( ampga ) to solve the reliability allocation problem of large and complicated software systems . finally , we experimented on the comity center subsystem , delivery center subsystem and system management subsystem of the project : the jiangsu province postal logistics information system
针对标准遗传算法存在着收敛速度慢、易陷入局部极小值等缺点，本文设计并实现了自适应多种群并行遗传算法（ ampga ） ，来解决大型、复杂软件系统的可靠性分配问题。最后，对“江苏省邮政物流信息系统开发”项目中的“礼仪中心子系统” 、 “递送中心子系统”及“系统管理子系统”进行了可靠性分配实验。 - This thesis suggests a process considered minimizes the population size as similar individuals occur in the fitter members of the population , which helps reduce the execution times for ga by removing the redundancy associated with the saturation effect found in the later generation . this thesis uses a method that adds dynamic penalty terms to the fitness function according to the optimal degree of solutions , so as to create a gradient toward a feasible suboptimal or even optimal solutions . on the basis of the difference of the biggest and the smallest of fitness of individual , modifying the fitness function in order to convergence is a satisfaction
动态调节种群大小，去掉遗传算法在迭代后期搜索产生的过多相似个体，达到减少计算时间的目的；按照解的优劣程度给适应度函数增加一个在ga搜索过程中动态改变的可变罚函数，给搜索最优解创造一个梯度，使遗传算法收敛到可行的较优解或最优解；根据适应度值最大和最小个体的差修正适应度函数，使适应度函数值适中不容易造成收敛太快、局部收敛或根本不收敛而变成随机搜索；为了避免“近亲繁殖”采用竞争择优的交叉操作；利用并行遗传算法的思想，提出一种自适应多子种群进化策略；提出人口汰新政策来解决类似甚至相同的个体的情况发生。 - On the basis of genetic algorithm , the author analyzes the implementation characters of parallel genetic algorithm in different application environments in detail . the key implementations of internet - based parallel genetic algorithm ( ipga ) are discussed , and the corresponding program is also given in c + + . in order to improve the performance of the algorithm , three important improvements of ipga are presented
论文以遗传算法为例，详细分析了不同应用平台下并行遗传算法的实现特点，着重探讨了基于internet的并行遗传算法( internet - basedparallelgeneticalgorithm ，简称ipga )实现中的关键问题，并给出具体程序实现。 - Ga has the common shortcomings while applied in large - scale network , such asconsuming huge calculation time , easy to be trapped by local fninimize and not so goodability of searching local optimal solution . the pseudo - parallel ga technology and adaptivechanging population size are used to generate ndtial populaton , thus elevating the quality ofinitial population and furthermore improving optimal solution , voltage / reactive is of localcharacteristic in actual power system , and this fetch oul decomposing sub - area ga accordingto network natural management region
提出采用变群体规模的伪并行遗传算法获得初始解群体，极大地改善了初始解群体的质量；根据无功/电压问题的区域性特点，按照电网的自然管理分区，实现了遗传算法的分区分解计算；将常规的二次规划模型的无功优化方法与遗传算法有机地结合，构成了独具特色的混合遗传算法。