摘要
当前社会经济下行风险增加,企业面临提升核心竞争力的压力与挑战,合理的车间布局,能减少企业在制品库存,提高空间利用率,降低生产成本。在传统SLP方法的基础上,对车间物流相互关系和非物流相互关系进行系统分析,并构建了物料搬运成本最小和非物流关系密切程度最大的多目标规划模型,结合粒子群算法,得出优化布局方案。通过实际应用案例,验证了优化方案的有效性。结果表明通过SLP和粒子群算法结合能有效解决车间布局优化问题,为企业解决布局问题提供参考。
With the increasing of economic downturn risk,enterprises are facing the pressure and challenges to improve their core competitiveness.Rational workshop layout can reduce work-in-process inventory,improve space utilization and reduce production costs.The relationship between workshop logistics and non-logistics was systematically analyzed base on the traditional SLP method,a multi-objective programming model with minimum material handling cost and maximum non-logistics relationship was constructed.The model was solved to obtain the optimal layout scheme by particle swarm optimization algorithm,the effectiveness of the optimization solution was verified by practical application cases.The results show that the combination of SLP and particle swarm algorithm can effectively solve the problem of workshop layout optimization,which can provide reference for enterprise.
作者
徐晓鸣
邓裕琪
吴绮萍
XU Xiaoming;DENG Yuqi;WU Qiping(School of Mechanical and Power Engineering,Guangdong Ocean University,Zhanjiang,Guangdong 524088,China;Shenzhen SUNYILG Intelligent Equipment Co.,Ltd.,Shenzhen,Guangdong 518106,China)
出处
《机电工程技术》
2020年第2期17-20,98,共5页
Mechanical & Electrical Engineering Technology
基金
广东省教育厅青年创新人才类项目(编号:2016KQNCX059).
关键词
车间布局
系统布置方法
粒子群算法
布局优化
workshop layout
systematic layout planning
particle swarm algorithm
layout optimization
