基于深度学习的散货船舶调度优化算法  

The Optimization Algorithm Based on Deep Learning

作　　者：刘宏策 沈阅 LIU Hongce;SHEN Yue(Tangshan Caofeidian District Gangqian Logistics Co.,Ltd.,Tangshan Hebei 063200,China;Hebei Yandayan Soft Information System Co.,Ltd.,Tangshan Hebei 063200,China)

机构地区：[1]唐山曹妃甸区港前物流有限公司,河北唐山063200 [2]河北燕大燕软信息系统有限公司,河北唐山063200

出　　处：《信息与电脑》2023年第18期52-54,共3页Information & Computer

摘　　要：为提升船舶停泊运行的时效性,提出基于深度学习的散货船舶调度优化算法。首先,制定散货船舶的进出作业流程,分析船舶调度作业的影响因素;其次,利用深度学习算法优化船舶调度,并提出调度方案;最后,进行实验分析。实验结果表明,该算法能够有效节约散货船舶在港口等待调度的准备时间,优于对照组。To improve the timeliness of ship berthing operations,a deep learning based optimization algorithm for bulk cargo ship scheduling is proposed.Firstly,establish the entry and exit operation process for bulk cargo ships and analyze the influencing factors of ship scheduling operations.Secondly,use deep learning algorithms to optimize ship scheduling and propose scheduling plans.Finally,conduct experimental analysis.The experimental results show that the algorithm can effectively save the preparation time for bulk cargo ships waiting for scheduling at the port,which is better than the control group.

关 键 词：深度学习 散货船舶 船舶调度 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]