基于图卷积网络求解开放车间调度问题的方法  

A Method for Solving Open Workshop Scheduling Problem Based on Graph Convolutional Network

作　　者：赵昊鑫 万烂军 崔雪艳[1,2] 李长云 ZHAO Haoxin;WAN Lanjun;CUI Xueyan;LI Changyun(College of Computer Science,Hunan University of Technology,Zhuzhou Hunan 412007,China;Hunan Key Laboratory of Intelligent Information Perception and Processing Technology,Hunan University of Technology,Zhuzhou Hunan 412007,China)

机构地区：[1]湖南工业大学计算机学院,湖南株洲412007 [2]湖南工业大学智能信息感知及处理技术湖南省重点实验室,湖南株洲412007

出　　处：《湖南工业大学学报》2024年第4期34-39,共6页Journal of Hunan University of Technology

基　　金：国家自然科学基金资助项目(61702177);湖南省教育厅优秀青年基金资助项目(21B0547);湖南省自然科学基金资助项目(2023JJ30217);湖南省教育厅科研基金资助重点项目(21A0356)。

摘　　要：传统的元启发式算法难以有效求解大规模开放车间调度问题(OSSP),为此提出了一种基于图卷积网络GCN求解OSSP的方法。首先,设计了基于GCN的开放车间调度模型,将OSSP的工序节点特征嵌入图中并对其进行多层卷积操作,有效获取了工序节点之间复杂的依赖关系。然后,为了提高求解大规模OSSP的效率和质量,提出了一种基于GCN的开放车间调度算法。实验结果表明,该方法能有效求解不同规模的OSSP实例,与元启发式算法相比,在求解大规模OSSP实例时该方法表现出更优秀的求解质量和效率。Due to the lower efficiency found in traditional metaheuristic algorithms for a solution of a large-scale open workshop scheduling problems(OSSP),a method based on graph convolution network(GCN)has thus been proposed to solve OSSP.Firstly,an open workshop scheduling model based on GCN has been designed,which incorporates the process node features of OSSP into the graph,to be followed by a multi-layer convolution operation on it,thus effectively obtaining the complex dependency relationships between process nodes.Next,in view of an improvement of efficiency and quality of solving large-scale OSSP,an open workshop scheduling algorithm has been proposed based on GCN.The experimental results show that this method can effectively solve OSSP instances of different scales.Compared with metaheuristic algorithms,the proposed method is characterized with a better solution quality and higher efficiency in solving large-scale OSSP instances.

关 键 词：开放车间调度 图卷积网络 元启发式算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]