Quick and situ-aware spatiotemporal scheduling for shipbuilding manufacturing

IF 1.4 4区 工程技术 Q4 ENGINEERING, MANUFACTURING
Junying He, Soon-Ik Hong, Seong-Hee Kim
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引用次数: 0

Abstract

Spatiotemporal scheduling of the block assembly process in shipbuilding is to determine temporal information including a time period when each block is under assembly and spatial information including an assigned bay and the placement of the block within the assigned bay. Due to a large number of discrete variables to optimize, finding an optimal schedule in a reasonably short time is almost impossible. Instead, we divide the problem into two phases where the first phase determines the bay assignment and processing start date for each block and the second phase determines the coordinates and rotation of each block in its assigned bay. Our objective is to find a block assembly schedule that minimizes the number of blocks that fail to be processed on time and unfairness in workloads across bays and days. The proposed algorithm is tested on six datasets of block information provided by Korea Shipbuilding & Offshore Engineering Co., Ltd. (KSOE). Our algorithm speeds up the scheduling process and finds schedules of higher quality compared to the original schedules that are manually planned by KSOE.

Abstract Image

用于造船业的快速和情景感知时空调度
造船业中船块装配过程的时空调度需要确定时间信息,包括每个船块进行装配的时间段,以及空间信息,包括分配的船坞和船块在分配船坞中的位置。由于需要优化的离散变量较多,在合理的短时间内找到一个最佳时间表几乎是不可能的。相反,我们将问题分为两个阶段,第一阶段确定每个区块的海湾分配和处理开始日期,第二阶段确定每个区块在其分配海湾中的坐标和旋转。我们的目标是找到一个区块装配时间表,最大限度地减少未能按时处理的区块数量以及不同海湾和不同日期之间工作量的不公平性。我们在韩国造船海洋工程有限公司(KSOE)提供的六个区块信息数据集上测试了所提出的算法。(KSOE) 提供的六个数据集进行了测试。与 KSOE 手工计划的原始计划相比,我们的算法加快了计划编制过程,并找到了质量更高的计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Scheduling
Journal of Scheduling 工程技术-工程:制造
CiteScore
3.80
自引率
10.00%
发文量
49
审稿时长
6-12 weeks
期刊介绍: The Journal of Scheduling provides a recognized global forum for the publication of all forms of scheduling research. First published in June 1998, Journal of Scheduling covers advances in scheduling research, such as the latest techniques, applications, theoretical issues and novel approaches to problems. The journal is of direct relevance to the areas of Computer Science, Discrete Mathematics, Operational Research, Engineering, Management, Artificial Intelligence, Construction, Distribution, Manufacturing, Transport, Aerospace and Retail and Service Industries. These disciplines face complex scheduling needs and all stand to gain from advances in scheduling technology and understanding.
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