共查询到20条相似文献,搜索用时 156 毫秒
1.
离心压缩机叶轮的形状优化设计 总被引:2,自引:0,他引:2
提出一种新的优化方法离心叶轮的形状优化问题,即在遗传算法中加入自适应算子调节个体变异概率,来保证搜索的全局性和种群的多样性。并在寻优过程中加入生物生长来加快其寻优速度。最后,采用遗传算法和改进的遗传算法-生物生长法两种方法,对叶轮进行优化设计。计算结果表明改进的遗传算法-生物生长法,在较少的优化时间得到最优解。 相似文献
2.
一种改进遗传算法及在结构优化设计中的应用 总被引:5,自引:0,他引:5
针对简单遗传算法中的线性适应度、恒定交叉与变异概率等不能动态地适应整个寻优过程,提出采用非线性适应度与自适应交叉、变异概率的改进遗传算法。以典型的遗传算法测试函数验证改进遗传算法的有效性与可行性,最后将改进遗传算法用于离散变量桁架结构优化设计,计算结果表明改进遗传算法是可行、有效的。 相似文献
3.
4.
针对传统遗传算法在求解非线性规划问题时局部搜索能力较弱,惩罚函数求解精度不高的缺陷,将非线性规划算法引入到遗传算法中,提出一种基于动态惩罚函数的非线性规划遗传算法,将遗传算法的全局寻优能力和非线性规划算法的局部寻优能力结合起来,并引入动态惩罚函数,根据不可行点到可行域的距离和可行度自适应的调整惩罚项的值,从而能够快速求出全局最优解。介绍了动态惩罚函数的设计、改进遗传算法的关键技术和流程。最后,以某型号汽车变速器的优化设计验证了算法的合理性。与传统遗传算法相比,改进后的遗传算法解的质量、收敛速度明显提高,因而为遗传算法的改进提供了一种新的思路。 相似文献
5.
6.
提出一种新型的遗传算法交叉算子,即单纯形交叉算子。这种算子实现了遗传算法与单纯形算法之间的结合,它能加快遗传算法的寻优速度,提高遗传算法定位最优解的精度。通过动态调整该算子的调用概率,可以方便地控制它的使用。本文还提出了一种所谓的“淘汰选择”,这种操作使得操作算子生成的新解不再是简单地取代其亲生父代个体,而是取代父代群体中的劣质个体。测试的算例表明该算子效果显著。 相似文献
7.
针对简单遗传算法中容易出现的早熟性收敛问题,采用“自适应算子”和“移民策略”相结合的办法对简单遗传算法进行改进,并且采取了“加速迭代”的操作,最后通过对Schaffer函数的计算表明,本文改进的遗传算法在保证全局收敛的同时有效地避免了早熟性收敛的发生。 相似文献
8.
基于改进遗传算法求解堆垛机路径优化问题 总被引:1,自引:0,他引:1
通过对遗传算法进行自适应改进,算出能够随时适应的遗传算子,克服了传统遗传算法的早熟收敛问题.通过运用序号法设定各货位在立体仓库中的位置,建立堆垛机拣选作业的数学模型,运用改进遗传算法对初始路径进行改进,得出最优解,并运用Matlab遗传算法工具箱对此进行仿真. 相似文献
9.
10.
遗传算法具有全局搜索能力强的特点,但易出现"早熟"现象;蚁群算法局部具有搜索能力强的特点.因此将遗传算法与蚁群算法结合,与此同时融合了云模型,提出一种适用于跨越越障式巡检机器人的求逆算法.为了提高算法的局部搜索能力及收敛速度,引入了网格划分策略的连续域蚁群算法;为了避免"早熟",采用了适应度值尺度变换;为了使参数自适应,采用了云模型进行修正.用遗传算法进行全局搜索,用蚁群算法进行局部迭代寻优,用云模型实现交叉算子和变异算子中参数的自适应.并以跨越机器人为对象,开展与遗传算法的对比实验,结果表明:该算法可以在避免局部收敛的基础上保证算法的稳定性以及提高收敛的速度和精度. 相似文献
11.
12.
Liang Zhang Ling Wang Da-Zhong Zheng 《The International Journal of Advanced Manufacturing Technology》2006,27(5-6):580-587
Genetic algorithms (GAs) are a class of effective parallel searching algorithms inspired by the idea of “survival of the fittest”,
which has been successfully applied to a variety of problems, especially in the fields of manufacturing and scheduling. However,
it is reported that traditional GAs often suffer from the weaknesses of premature convergence as well as parameter and operator
dependence. So far, many improved methods with adaptive parameters or hybrid structures have been proposed, but there is little
literature considering the adaptive control of genetic operators. In this paper, an adaptive GA (AGA) with multiple operators
is proposed for flowshop scheduling, which is a typical NP-hard optimisation problem with many industrial applications and
has been widely studied in both academic and engineering fields. In AGA, multiple different genetic operators are employed
in an adaptive hybrid way to enhance the exploration and exploitation abilities so as to prevent premature convergence and
achieve superior performance. It especially important to stress that the utilising ratio of each operator for hybridisation
is adaptively and dynamically controlled during the evolutionary searching process. Simulation results based on benchmarks
demonstrate the effectiveness of AGA by contrast with traditional GAs. And the effect of the adaptive control of the operator
and the effects of some parameters on the optimisation performance are discussed as well. 相似文献
13.
14.
为优化航天器中隔振系统的隔振参数,提出了一种基于自适应遗传算法的优化方法。在只考虑单条支腿的前提下,建立了主动隔振系统的动力学模型,通过拉普拉斯变换得到了上平台输出的力对下平台控制力的传递函数,并获得待优化的参数。将参数优化问题转化成数值优化问题,利用最大熵法生成算法的目标函数;采用新的选择算子来避免算法早熟;提出自适应交叉算子和自适应高斯变异算子来保证种群多样性;通过优胜劣汰和种群迁移法则来提高算法的全局收敛性。最后,通过仿真实例对算法的有效性进行验证,结果表明:和传统的遗传算法相比,本算法的收敛速度快、优化效果好。 相似文献
15.
传统空间遥操作系统中从端机械臂的运动速度完全取决于操作者的操作速度。为了提高空间遥操作系统的安全性,提出了一种基于操作者操作速度识别的自适应速度控制方法。结合深度学习的理论,提出了一种基于卷积神经网络(CNN)和门控循环单元(GRU)神经网络的融合模型来对操作者的速度进行识别分类。选取了九位受试者构建操作者速度样本库,将操作者的操作速度分为3类,最终识别准确率达到92.71%;并且在此基础上使用串级PID实现从端机械臂的自适应速度控制。实验表明:该模型对新操作者也可以准确识别,同时该模型准确性优于卷积神经网络和循环神经网络(RNN)的融合模型,实时性优于卷积神经网络和长短期记忆(LSTM)神经网络的融合模型;基于该模型的自适应速度控制可以在保证从端机械臂运动轨迹不变的前提下,降低机械臂的末端线速度,有助于提高空间遥操作系统的安全性。 相似文献
16.
Shun-Fa Hwang Ya-Chu Hsu Yuder Chen 《Journal of Mechanical Science and Technology》2014,28(8):3163-3169
A genetic algorithm for the optimization of composite laminates is proposed in this work. The well-known roulette selection criterion, one-point crossover operator, and uniform mutation operator are used in this genetic algorithm to create the next population. To improve the hill-climbing capability of the algorithm, adaptive mechanisms designed to adjust the probabilities of the crossover and mutation operators are included, and the elite strategy is enforced to ensure the quality of the optimum solution. The proposed algorithm includes a new operator called the elite comparison, which compares and uses the differences in the design variables of the two best solutions to find possible combinations. This genetic algorithm is tested in four optimization problems of composite laminates. Specifically, the effect of the elite comparison operator is evaluated. Results indicate that the elite comparison operator significantly accelerates the convergence of the algorithm, which thus becomes a good candidate for the optimization of composite laminates. 相似文献
17.
Assembly line balancing based on an adaptive genetic algorithm 总被引:2,自引:2,他引:0
Jianfeng Yu Yuehong Yin 《The International Journal of Advanced Manufacturing Technology》2010,48(1-4):347-354
An adaptive genetic algorithm is presented as an intelligent algorithm for the assembly line balancing in this paper. The probability of crossover and mutation is dynamically adjusted according to the individual’s fitness value. The individuals with higher fitness values are assigned to lower probabilities of genetic operator, and vice versa. Compared with the traditional heuristic algorithms, the adaptive genetic algorithm has effective convergence and efficient computation speed. The computational results demonstrate that the proposed adaptive genetic algorithm is an effective algorithm to deal with the assembly line balancing to obtain a smoother line. 相似文献
18.
针对压电陶瓷的迟滞特性可使微夹钳难以获得良好的位移控制的问题,提出自适应逆控制策略。推导了压电悬臂位移特性的理论模型;采用自适应最小均方算法滤波器建立了压电悬臂的基于Backlash算子的迟滞环正逆模型,并以此为基础建立了微夹钳位移的自适应逆控制系统。样机测试和跟踪实验结果验证了所建立的理论模型和迟滞环模型的正确性,以及控制系统良好的自学习能力和控制效果。 相似文献
19.
The optimal tuning of adaptive flap controller can improve adaptive flap control performance on uncertain operating environments, but the optimization process is usually time-consuming and it is difficult to design proper optimal tuning strategy for the flap control system (FCS). To solve this problem, a novel adaptive flap controller is designed based on a high-efficient differential evolution (DE) identification technique and composite adaptive internal model control (CAIMC) strategy. The optimal tuning can be easily obtained by DE identified inverse of the FCS via CAIMC structure. To achieve fast tuning, a high-efficient modified adaptive DE algorithm is proposed with new mutant operator and varying range adaptive mechanism for the FCS identification. A tradeoff between optimized adaptive flap control and low computation cost is successfully achieved by proposed controller. Simulation results show the robustness of proposed method and its superiority to conventional adaptive IMC (AIMC) flap controller and the CAIMC flap controllers using other DE algorithms on various uncertain operating conditions. The high computation efficiency of proposed controller is also verified based on the computation time on those operating cases. 相似文献