| 改进的多目标粒子群算法优化设计及应用 |
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| 引用本文： | 张兰勇,刘胜,于大泳.改进的多目标粒子群算法优化设计及应用[J].电波科学学报,2011(4):789-795,824. |
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| 作者姓名： | 张兰勇 刘胜 于大泳 |
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| 作者单位： | 哈尔滨工程大学自动化学院; |
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| 基金项目： | 国家自然科学基金(51079033); 中国博士后科学基金(20080430888) |
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| 摘 要： | 针对粒子群算法存在易陷入局部最优点的缺点,提出了一种改进的带变异算子的多目标粒子群优化算法。采用非支配排序策略和动态加权法选择最优粒子,引导种群飞行,提高帕累托(Pareto)最优解的多样性。与其他优化算法相比,该算法易于实现并且计算速度更快。通过计算Pareto前沿最优解设计最佳多层电磁吸收体,在吸收体的厚度与反射系数之间取得最佳折衷。通过对反射系数函数与吸收体厚度函数测试验证,该算法能够在保持优化解多样性的同时具有较好的收敛性。
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| 关 键 词： | 多目标粒子群算法 变异算子 电磁吸收体 优化设计 |
Application and optimization design of improved multi-objective particle swarm |
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| ZHANG Lan-yong LIU Sheng YU Da-yong.Application and optimization design of improved multi-objective particle swarm[J].Chinese Journal of Radio Science,2011(4):789-795,824. |
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| Authors: | ZHANG Lan-yong LIU Sheng YU Da-yong |
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| Affiliation: | ZHANG Lan-yong LIU Sheng YU Da-yong (College of Automation,Harbin Engineering University,Heilongjiang Harbin 150001,China) |
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| Abstract: | An improved multi-objective particle swarm optimization(MOPSO)is presented in the paper.To overcome the shortcoming of particle swarm optimization(PSO) algorithm,that plunging into the local mimimum,an advanced PSO algorithm with mutation operator is introduced.Non-dominated sorting and dynamic aggregate method are used to guide the flight of particles and improve the diversity of the Pareto optimal solutions.Compared with other optimization algorithms,the proposed method is simple and fast.Use of MOPSO for... |
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| Keywords: | multi-objective partical swarm mutation operator electromagnetic absorber optimization design |
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