摘要
针对检修计划多目标多约束特性,以系统运行总费用最小为目标建立经济性模型,并利用改进的多蚁群伪并行寻优算法IMCVPOA求解。引入信息素平滑机制、状态表记忆机制和惩罚因子,通过设计迁移算子,使多个子蚁群并行、协同寻优,从而使算法跳离局部最优解。仿真结果证明,模型具有良好的经济性。
Aimed at the multi-objective and multi-constraint of maintenance schedule, an economic model is designed to minimize the operation cost and improved multi-ant colony virtual parallel optimization algorithm is proposed to solve the model By introducing an immigrant operator , state memory mechanism and penalized factors, the parallel and cooperating optimization of children ant colonies are obtained to avoid the partial optimum relation. The simulation results indicate that the model posesses better economy.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2009年第4期120-124,共5页
Proceedings of the CSU-EPSA
关键词
蚁群算法
信息素平滑
迁移算子
惩罚因子
状态表记忆机制
改进的多蚁群伪并行寻优算法
ant colony algorithm
pheromone flatness
immigrant operator
penalized factors
state memory mechanism
Imhroved multi-ant colony virtual parallel optimization algorithm（IMCVPOA）
