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| 人工免疫粒子群算法在系统可靠性优化中的应用 | |
| 引用本文： | 阮旻智,李庆民,王红军,黄傲林,马杰.人工免疫粒子群算法在系统可靠性优化中的应用[J].控制理论与应用,2010,27(9):1253-1258. |
| 作者姓名： | 阮旻智 李庆民 王红军 黄傲林 马杰 |
| 作者单位： | 1. 海军工程大学,兵器工程系,湖北,武汉,430033 2. 海军大连舰艇学院,作战指挥系,辽宁,大连,116018 3. 海军工程大学,核能科学与工程系,湖北,武汉,430033 |
| 基金项目： | 国家自然科学基金资助项目(70871117); 总装预研基金资助项目(513040303). |
| 摘 要： | 为了优化舰载装备系统在其设计初期的可靠性,根据模糊优选理论,建立了基于正负理想方案的可靠性分配的多指标模糊优化模型.针对基本粒子群(PSO)算法易陷入早熟状态以及群体缺乏多样性等不足之处,将人工免疫系统(AIS)原理与改进的粒子群算法有机结合,并对粒子的飞行速度进行控制,提出一种基于人工免疫的粒子群算法(AI-PSO).将该算法应用于系统可靠性优化求解中,仿真试验结果表明,相比其他算法而言,该算法具有较强的全局搜索能力,其优化结果更为合理. |
| 关 键 词： | 人工免疫系统 粒子群算法 系统可靠性 优化 |
| 收稿时间： | 2009/7/24 0:00:00 |
| 修稿时间： | 2009/11/28 0:00:00 |
Application of artificial immune particle-swarm-optimization algorithm to system-reliability optimization |
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| RUAN Min-zhi,LI Qing-min,WANG Hong-jun,HUANG Ao-lin and MA Jie.Application of artificial immune particle-swarm-optimization algorithm to system-reliability optimization[J].Control Theory & Applications,2010,27(9):1253-1258. | |
| Authors: | RUAN Min-zhi LI Qing-min WANG Hong-jun HUANG Ao-lin and MA Jie |
| Affiliation: | Department of Weaponry Engineering, Naval University of Engineering,Department of Weaponry Engineering, Naval University of Engineering,Operational Command Department, Dalian Naval Academy,Department of Weaponry Engineering, Naval University of Engineering,Department of Nuclear Energy Science & Engineering, Naval University of Engineering |
| Abstract: | To optimize the reliability of a shipborne equipment system in the early stage of design, we employ the fuzzy-optimum-selection theory to build a fuzzy multi-targets-optimization model for this equipment system based on the plus-and-minus ideal project. Because the particle-swarm-optimization(PSO) algorithm is prone to be trapped into a local extremum and the colony lacks in diversity, we combine the theory of artificial-immune-system(AIS) and the improved PSO algorithm to put forward the artificial-immune-particle-swarm-optimization(AIPSO) to control the flight-velocity of particles. This algorithm has been applied to the system-reliability optimization; the simulation results show that it has a better global search capability and provides more rational optimization results over other algorithms. |
| Keywords: | artificial immune system particle swarm optimization algorithm system reliability optimization |
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