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.
To optimize the reliability of a shipbome 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.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2010年第9期1253-1258,共6页
Control Theory & Applications
基金
国家自然科学基金资助项目(70871117)
总装预研基金资助项目(513040303)
关键词
人工免疫系统
粒子群算法
系统可靠性
优化
artificial immune system
particle swarm optimization algorithm
system reliability
optimization
