基于改进PSO的压铸自动化生产线优化调度  

Optimal Scheduling of Automatic Die Casting Production Line Based on Improved PSO

作　　者：陶丽华[1] 迟晓晨 谷东伟[1] TAO Lihua;CHI Xiaochen;GU Dongwei(School of Mechanical and Electrical Engineering,Changchun University of Technology,Changchun 130012,China)

机构地区：[1]长春工业大学机电工程学院,长春130012

出　　处：《机械工程师》2021年第9期4-7,10,共5页Mechanical Engineer

基　　金：工业与信息化智能制造新模式项目(2016080)。

摘　　要：针对某压铸自动化生产线调度的实际需求,考虑运输机的速度对生产调度和环境的影响,以设备总空闲时间、设备负荷均衡、产出零件数和运输机等待时间为优化目标,建立压铸自动化生产线多目标并行机调度数学模型,提出一种求解多目标并行机调度的改进的粒子群算法。通过引入动态惯性权重、个体极值和群体极值的扰动、建立极值库,提高粒子群算法的全局寻优能力。通过模拟退火算法对粒子进行局部优化,避免算法提前收敛。最后,通过实验验证了算法的有效性。According to the actual demand of a die casting automatic production line scheduling,considering the impact of transport speed on production scheduling and the environment,taking the total idle time of equipment,equipment load balance,number of castings produced and waiting time of transporters as optimization objectives,a multi-objective parallel machine scheduling mathematical model for die casting automation production line is established,an improved particle swarm optimization algorithm for multi-objective parallel machine scheduling is proposed.By introducing the dynamic inertia weight,the perturbation of individual extremum and population extremum,and establishing the extremum library,the global optimization ability of the particle swarm optimization algorithm is improved,particle optimization is performed by simulated annealing algorithm to avoid the convergence of the algorithm in advance.Finally,lots of experiments prove the effectiveness of the algorithm.

关 键 词：压铸自动化生产线 并行机调度 多目标优化 改进粒子群算法 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]