人工免疫粒子群算法在系统可靠性优化中的应用  

Application of artificial immune particle-swarm-optimization algorithm to system-reliability optimization

作　　者：阮旻智[1] 李庆民[1] 王红军[2] 黄傲林[1] 马杰[3] 

机构地区：[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

出　　处：《控制理论与应用》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)

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.

关 键 词：人工免疫系统 粒子群算法 系统可靠性 优化 

分 类 号：O224[理学—运筹学与控制论]