摘要
智能制造车间以自动导引车(Automated guided vehicle,AGV)作为重要的物流运输载体,现有的研究多采用智能制造车间布局和AGV路径分步骤优化的方式,导致AGV运行效率不高,无法达到最优布局等问题。为此,以智能制造流水线车间为对象,设计了以物流量最小及AGV路径最短为目标的考虑AGV路径规划的智能制造流水线布局优化模型;研究了改进遗传算法的交叉算子,将编码转变为矩阵形式建立邻接表,改进临边重组法;研究了改进遗传算法的变异因子,将基因编码划分为若干个基因串,在基因串内进行变异操作。提高了算法的效率和精度,并用算例验证了其可行性和有效性。
AGV(Automated guided vehicle)is the important logistics tools for the intelligent manufacturing workshop.The intelligent manufacturing workshop layout and AGV path planning are optimized separately in the current researches,which results in the low operation efficiency of AGV and the inability to achieve the optimal layout.Taking the intelligent manufacturing flow shop as the object,an optimization model which aims at the minimum material flow and the shortest AGV path is established.The crossover operator of improved genetic algorithm is studied,the coding is transformed into matrix form,the adjacency table is established,and the edge recombination method is improved.The mutation factor of improved genetic algorithm is studied,the gene code is divided into several gene strings,and the mutation operation is carried out in the gene string.The method is verified by an example.
作者
毕娜
BI Na(College of Mechanical Engineering,Zhejiang University of Technology,Hangzhou 310023,China)
出处
《浙江工业大学学报》
CAS
北大核心
2022年第5期568-573,共6页
Journal of Zhejiang University of Technology
基金
浙江省教育厅一般科研项目(Y201941061)。
