基于元胞自动机的块车间空间调度建模与优化

IF 2.5 Q2 ENGINEERING, INDUSTRIAL IET Collaborative Intelligent Manufacturing Pub Date : 2023-02-21 DOI:10.1049/cim2.12075
Yong Chen, Xuanhao Lin, Wenchao Yi
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引用次数: 0

摘要

砌块制造是对造船效率影响最大的工序,因此砌块空间调度作为提高造船效率的关键问题被广泛研究。船舶空间调度问题研究的是时间与空间的耦合特性。很难平衡这两个方面。针对船舶企业空间调度问题的特点,导入以时间为第三维的三维空间,构建具有演化规则的元胞自动机模型,包括形状优化规则、基于聚类或边缘规则的布局规则、先到先服务调度规则等。目标是实现最小的总完成时间,最大的空间和机器利用率,以及最少的延迟块数。以某造船企业某块车间的实际数据为例,通过与其他算法的统计分析对比,验证了该算法的可行性和有效性。
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Block workshop spatial scheduling based on cellular automata modelling and optimization

Block fabrication is the process that has the greatest impact on shipbuilding efficiency, so block spatial scheduling is widely studied as the key to improving shipbuilding efficiency. The shipbuilding spatial scheduling problem addresses the coupling characteristics of time and space. It is difficult to balance these two aspects. Based on the characteristics of spatial scheduling problems in shipbuilding enterprises, a three-dimensional space that uses time as the third dimension is imported, and a cellular automata model along with some evolutionary rules is built, which includes shape optimization rules, cluster or edge rule-based layout rules, and First Come First Service dispatching rules. The objectives are to achieve the minimum total completion time, the largest utilization of space and machine, and the least number of delay blocks. Taking the real data in a block workshop of a shipbuilding enterprise as an example, the feasibility and effectiveness of the algorithm are verified by comparing the statistical analysis with other algorithms.

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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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