摘要
考虑到当前数据的大规模特性,传统的调度方法已不适应市场迅速变化和产品快速更新的需求,粒子群算法作为典型的智能优化算法,在解决此类问题中突显了优势。对粒子群算法及其演化进行分析,得出制造调度系统中的诸多粒子群算法特征,找到粒子群算法求解制造调度系统问题的进一步研究方向。
Considering the large-scale characteristics of current data,traditional scheduling methods can no longer meet the needs of rapid market changes and product updates.Particle Swarm Optimization,as a typical intelligent optimization algorithm,has highlighted its advantages in solving such problems.Based on the analysis of particle swarm optimization and its evolution,the characteristics of many particle swarm optimization methods in manufacturing scheduling system are obtained,and the further research direction of particle swarm optimization for solving manufacturing scheduling system problems is found.
作者
王楚楚
臧海娟
WANG Chuchu;ZANG Haijuan(Jiangsu University of Technology,College of Mechanical Engineering,Changzhou Jiangsu 213001,China;Jiangsu University of Technology,College of Computer Engineering,Changzhou Jiangsu 213001,China)
出处
《装备制造技术》
2021年第9期21-24,30,共5页
Equipment Manufacturing Technology
基金
中科专项培育引导项目(ZK-PY-2019-04)
平湖市科技计划项目(GX202005)。
关键词
粒子群算法
制造调度系统问题
智能优化
particle swarm optimization
Manufacturing scheduling system problem
intelligent optimization
