提出一种具有逻辑时序特征的微粒群优化算法，并将其应用于半导体封装生产线的工序参数优化中。
A kind of particle swarm optimization method with the characteristic of logical time-sequenced is proposed and applied to procedure parameters optimization of semiconductor assembly product line.
目前微粒群算法已广泛应用于函数优化、神经网络训练、数据挖掘、模糊系统控制以及其他的应用领域。
Recently, Particle Swarm optimization is applied into function optimization, Neural Networks, data mining, Fuzzy Control System and other application field.
论文研究结果丰富了不确定优化理论，拓宽了微粒群优化算法的应用领域，为PSO在复杂不确定系统中的应用提供了有益的指导。
Research results of this dissertation enrich theory of the uncertain optimization, expand application domain of PSO, and provide beneficial guides for applying PSO in complicated uncertain systems.
论文研究结果丰富了不确定优化理论，拓宽了微粒群优化算法的应用领域，为PSO在复杂不确定系统中的应用提供了有益的指导。
Research results of this dissertation enrich theory of the uncertain optimization, expand application domain of PSO, and provide beneficial guides for applying PSO in complicated uncertain systems.
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