基于改进粒子群算法的车间物料配送方法研究  

Research on Workshop Material Delivery Method Based on Improved Particle Swarm Optimization

作　　者：杨倩 陈再良[1] YANG Qian;CHEN Zai-liang(School of Mechanical and Electrical Engineering,Soochow University,Jiangsu Suzhou 215137,China)

机构地区：[1]苏州大学机电工程学院,江苏苏州215137

出　　处：《机械设计与制造》2022年第8期238-241,共4页Machinery Design & Manufacture

基　　金：江苏省科技厅资助项目(BY2016043-02,BA2014004)。

摘　　要：针对含多种物料搬运设备的车间物料配送问题,考虑搬运设备运量约束、物料需求和线边缓存约束以及时间约束,构建了以搬运成本和线边库存成本最小化、装载率最大化为优化目标的多种物料搬运设备协同调度物料配送模型;设计改进粒子群算法并给出使用此算法求解模型的具体实现过程。以助力器装配车间为例,验证了模型和算法的有效性,并将其与自适应粒子群算法进行对比,实验结果表明,改进粒子群算法的解优于自适应粒子群算法且运行时间短。Aiming at the material delivery problem in the workshop with multi-class material handling equipment,a collaborative material dispatching model of material handling equipment is established with the optimization objectives of minimizing the inventory holding cost and the delivery cost of equipment and maximizing the load ratio,considering the constraints of traffic volume,material demands and line-side buffers as well as time.The improved particle swarm optimization algorithm is designed and the detail realization process with this algorithm is presented.The validity of this model and algorithm is verified by a case of booster assembly workshop,and compared with the adaptive particle swarm optimization algorithm,the improved particle swarm optimization algorithm has superior solution and shorter running time which is showed in simulation results.

关 键 词：物料配送 多种物料搬运设备 协同调度 改进粒子群算法 

分 类 号：TH18[机械工程—机械制造及自动化] TP301[自动化与计算机技术—计算机系统结构]