Application of artificial immune particle-swarm-optimization algorithm to system-reliability optimization
人工免疫粒子群算法在系统可靠性优化中的应用

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.