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Multi-objective Gaussian particle swarm algorithm optimization based on niche sorting for actuator design:

机译:基于小生境排序的多目标高斯粒子群算法在执行器设计中的优化:

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摘要

With the fast-developing electromagnetic valve actuator, multi-objective optimal methods for actuator problems have been widely concerned in recent years. This article presents a modified multi-objective particle swarm optimization algorithm based on sorting method and employs it to the product design of the actuator. The simulation results show that modified optimization algorithm could obtain a better Pareto front in contrast to classical non-dominated sorting genetic algorithm-II method, meanwhile preserving the high capacity of fast solving of non-dominated solutions.
机译:随着电磁阀致动器的快速发展,近年来,针对致动器问题的多目标优化方法已受到广泛关注。本文提出了一种基于分类的改进多目标粒子群算法,并将其应用于执行器的产品设计。仿真结果表明,与经典的非支配排序遗传算法-II方法相比,改进的优化算法可以获得更好的Pareto前沿,同时保留了快速求解非支配解决方案的高容量。

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