共查询到20条相似文献,搜索用时 830 毫秒
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文中针对搅拌摩擦焊,进行了搅拌头的形状选择,建立了搅拌头优化的数学模型和约束条件,提出了基于遗传算法的搅拌头尺寸多目标优化算法,并进行了忧化实例分析,得到了合理的搅拌头尺寸参数。 相似文献
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离散变量桁架结构拓扑优化的混合遗传算法 总被引:4,自引:0,他引:4
为了避免结构拓扑优化过程中杆件和节点的增删带来的计算上的麻烦,在对桁架结构受力分析的基础上,提出一种启发式方法,以快速产生符合机动性要求的拓扑结构形式;然后在既定的拓扑结构形式下采用混合遗传算法——拟满应力遗传算法进行截面优化。该方法通过在遗传算法中嵌入拟满应力算子,同时对基本遗传算法采用最优个体保留、最差个体替换和控制种群个体差异等改进措施,有效提高遗传算法求解的效率和质量。算例结果表明,该方法用于离散变量桁架结构拓扑优化是有效的。 相似文献
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海洋磁力仪的本体磁性校正是磁力仪应用系统的核心技术,尤其当载体磁性发生改变后,其现场的校正算法是影响其应用有效性的关键。先分析了搭载有三轴磁通门磁力仪的水下勘探系统的主要磁干扰源,描述了相应的磁校正模型,简明扼要地介绍了椭球拟合、粒子群、遗传及粒子群遗传混合等算法,并逐一通过MATLAB予以实现。最后使用水下载体在西南印度洋的作业数据对上述算法进行功能性验证。由校正前后的数据波动情况、均方根误差值和相对误差值可知,磁校正领域混合算法校正效果相对较佳,能提高磁力仪传感器的测量有效性。 相似文献
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基于MATLAB遗传算法的电磁轴承控制系统优化 总被引:3,自引:0,他引:3
提出基于MATLAB遗传算法的电磁轴承控制系统的PID参数寻优方法,仿真结果证明遗传算法寻优后的PID控制器较常规PID控制器具有更好的控制特性,并且算法简单,具有广泛的推广使用价值。 相似文献
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Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem. 相似文献
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Yee-Ming Chen Chun-Ta Lin 《The International Journal of Advanced Manufacturing Technology》2007,35(5-6):610-620
The particle swarm optimization (PSO) approach has been successfully applied in continuous problems in practice. However,
its application on the combinatorial search space is relatively new. The component assignment/sequencing problem in printed
circuit board (PCB) has been verified as NP-hard (non-deterministic polynomial time). This paper presents an adaptive particle
swarm optimization (APSO) approach to optimize the sequence of component placements on a PCB and the assignment of component
types to feeders simultaneously for a pick-and-place machine with multiple heads. The objective of the problem is to minimize
the total traveling distance (the traveling time) and the total change time of head nozzle. The APSO proposed in the paper
incorporates three heuristics, namely, head assignment algorithm, reel grouping optimization and adaptive particle swarm optimization.
Compared with the results obtained by other research, the performance of APSO is not worse than the performance of genetic
algorithms (GA) in terms of the distance traveled by the placement head. 相似文献
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冲裁件的排样是一个NP问题,在工业界具有广泛的需求.从矩形包络和遗传模拟退火算法这两个角度探讨了包含不规则形状的冲裁件的排样算法.随着冲压设备的不断发展,二维冲裁件的组合优化排样将会得到越来越广泛的普及和应用. 相似文献
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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
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漏磁检测中励磁结构的磁化能力是影响漏磁传感器缺陷检测能力的一个重要因素。根据交流漏磁检测原理,建立二维漏磁检测参数化有限元仿真模型,研究磁心的形状和尺寸、励磁线圈的位置和绕组长度、磁屏蔽层厚度等励磁结构参数对漏磁检测信号的影响。同时,将参数化有限元分析与遗传优化算法相结合,发展一种励磁结构尺寸参数的有限元模拟遗传优化设计方法,实现了漏磁传感器中磁极间距与磁极宽度等关键尺寸的优化。仿真及检测试验结果表明,传感器的励磁结构参数对漏磁检测结果具有很大影响,优化后的励磁结构可有效提高漏磁传感器的缺陷检测性能。提出的基于参数化有限元的遗传优化方法为漏磁检测中其余影响参数的优化提供了可行的参考方法。 相似文献
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可以并行分拣多个客户订单的"货到人"分拣系统中,每个客户包含多个订单,客户要求按订单排序依次收货。为提高该系统的分拣效率,以最小化料箱出入库数量为目标,从订单排序和客户分批两方面进行优化。分别建立两个0-1整数规划模型解决多客户同时拣选时的订单排序优化和客户分批优化问题;针对客户分批问题,又提出种子算法和遗传算法来解决。设计试验检验了不同客户数量、客户订单数量、总品项数量时订单排序模型和客户分批算法的优化效果。试验结果表明,0-1整数规划模型优化订单排序,可提高效率约15%,具有有效性;客户分批优化方面,0-1整数规划模型、遗传算法和种子算法都可以不同程度地提高系统效率,分别适合不同问题规模和时间要求的场景。 相似文献
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In the present research, the reliability-based design optimization (RBDO) of labyrinth weirs has been investigated. The optimization problem is formulated such that the optimal shape of trapezoidal labyrinth weir described by a number of variables is found by minimizing the volume of the trapezoidal labyrinth weir and maximizing the reliability index. The constraint conditions are the weir geometric shape and its different ratios. In order to achieve this purpose, a framework is presented whereby non-dominated sorting genetic algorithm (NSGA-II) is integrated with monte carlo simulation (MCS) method to solve the RBDO approach of trapezoidal labyrinth weirs. The proposed method is applied to UTE Dam labyrinth weir, and the results are compared with the real one. The results show the need for design based on reliability in the labyrinth weirs that propose using RBDO for weir design. The results showed that RBDO approach can achieve a more reliable design in addition to reducing the volume of the trapezoidal labyrinth weir. Finally, the sensitivity analysis of the parameters effective on the reliability index revealed that three design variables of weir width, total upstream head and discharge coefficient are the main parameters affecting weir RBDO solution. 相似文献
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José Elias Claudio Arroyo Ana Amélia de Souza Pereira 《The International Journal of Advanced Manufacturing Technology》2011,55(5-8):741-753
This paper presents a multi-objective greedy randomized adaptive search procedure (GRASP)-based heuristic for solving the permutation flowshop scheduling problem in order to minimize two and three objectives simultaneously: (1) makespan and maximum tardiness; (2) makespan, maximum tardiness, and total flowtime. GRASP is a competitive metaheuristic for solving combinatorial optimization problems. We have customized the basic concepts of GRASP algorithm to solve a multi-objective problem and a new algorithm named multi-objective GRASP algorithm is proposed. In order to find a variety of non-dominated solutions, the heuristic blends two typical approaches used in multi-objective optimization: scalarizing functions and Pareto dominance. For instances involving two machines, the heuristic is compared with a bi-objective branch-and-bound algorithm proposed in the literature. For instances involving up to 80 jobs and 20 machines, the non-dominated solutions obtained by the heuristic are compared with solutions obtained by multi-objective genetic algorithms from the literature. Computational results indicate that GRASP is a promising approach for multi-objective optimization. 相似文献