Abstract
According to fuzzy optimum selection theroy, the Euclidean distance from feasible projects to the ideal project and the minus-ideal project is regarded as evaluation criterion for establishing the fuzzy multi-targets optimization model. It can be known that particle swarm optimization(PSO) algorithm is easy to get in local extremum and the particles lack diversity through the analysis of its constringency. The particles’ velocity is controlled to improve the deficiencies of this algorithm. The theory of artificial immune system(AIS) and the improved particle swarm optimization algorithm are combined to put forward a new algorithm, artificial immune particle swarm optimization(AI-PSO). This method is applied to the solution of system reliability optimization, and the simulation result show that this algorithm has better capability of entire range search and the optimization result is more reasonable compared to other algorithms.
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