摘要
针对企业对订购期最低资金占用的订购参数寻优需求,应用具有量子特征的粒子群优化算法(QPSO),建立有效的粒子结构和适应度函数,实现在随机订购提前期寻找具有最低资金占用率的最优订购参数组合。实验和实际运行结果表明,因实际问题的多样性而使求解空间处于不确定的量子空间时,QPSO算法收敛稳定且快速。
According to the demand of minimum bankroll engross rate of the order forward scheduled time optimization, the quantum particle swarm optimization algorithm is used, particle structure and fitness function is established, the optimized combination of order parameter of random order forward scheduled time is achieved. The experimental result shows that the algorithm has more stable convergent characteristic and better convergent speed when applied in the dicey quantum inter space bring by the diversity of practical issue.
出处
《计算机工程与设计》
CSCD
北大核心
2007年第15期3656-3658,共3页
Computer Engineering and Design
关键词
动态优化
优化算法
粒子特性
粒子维度
适应度函数
dynamic optimization
optimization algorithm
characteristic of particle
dimensionality of particle
fitness function
