钕铁硼企业生产工单组炉的最佳优先和变邻域搜索算法

doi:10.11949/j.issn.0438-1157.20171578

化工学报 ›› 2018, Vol. 69 ›› Issue (3): 1207-1214.DOI: 10.11949/j.issn.0438-1157.20171578

钕铁硼企业生产工单组炉的最佳优先和变邻域搜索算法

刘业峰^1,2, 柴天佑³

1 沈阳工学院数控机床信息物理融合与智能制造辽宁省重点实验室, 辽宁抚顺 113122;
2 沈阳工学院机械与运载学院, 辽宁抚顺 113122;
3 东北大学流程工业综合自动化国家重点实验室, 辽宁沈阳 110004

收稿日期:2017-11-29 修回日期:2017-12-06 出版日期:2018-03-05 发布日期:2018-03-05
通讯作者: 刘业峰
基金资助:
国家自然科学基金项目（61603262，61403071）；中国博士后科学基金特别资助项目（2015T80798）；中国博士后科学基金面上项目（2014M552040）；辽宁省教育厅科技项目（L2015372）。

The best priority and variable neighborhood search algorithm for production furnace grouping in NdFeB enterprises

LIU Yefeng^1,2, CHAI Tianyou³

1 Liaoning Key Laboratory of Information Physics Fusion and Intelligent Manufacturing for CNC Machine, Shenyang Institute of Technology, Fushun 113122, Liaoning, China;
2 College of Mechanical and Vehicle Engineering, Shenyang Institute of Technology, Fushun 113122, Liaoning, China;
3 State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, Liaoning, China

Received:2017-11-29 Revised:2017-12-06 Online:2018-03-05 Published:2018-03-05
Supported by:
supported by the National Natural Science Foundation of China (61603262, 61403071), the Postdoctoral Science Foundation of China (2015T80798, 2014M552040) and Program Funded by Liaoning Province Education Administration (L2015372).

摘要/Abstract

摘要：

钕铁硼生产企业的生产工单组炉问题是企业生产组织面临的首要问题，组炉结果的好坏直接影响企业的生产效率。本文基于生产工单组炉的实际需求，建立了组炉的目标、面临的约束和相应决策变量的数学模型。针对生产工单组炉的具体问题，提出了基于最佳优先和变邻域搜索的生产工单组炉算法。该算法有3个组成部分，分别是确定生产工单组炉顺序的多层快速排序算法，生产工单组炉的最佳优先和变邻域搜索算法，不同牌号库存备料生产的规则的启发式算法。采用本文的算法，针对20个甩带生产工单的组炉问题，生产工单组炉的交货期偏差、各订单加工的优先级偏差和不同订单的牌号偏差和由58降低到42，下降率为27.59%；牌号的备料达标率由4个上升为6个，提高率为50%。通过对40个生产工单的组炉结果与人工组炉结果的对比，发现组炉结果减少2个炉次。将本文算法与改进的离散粒子群算法，和声变邻域搜索算法和自适应变邻域搜索算法的对比分析，也表明了本文算法的有效性，证明了所建立数学模型的正确性。

关键词: 钕铁硼, 组炉, 最佳优先, 整体优化, 生产制造, 模型

Abstract:

Production furnace grouping is critical in routine operation of NdFeB processes and the grouping results directly affect production efficiency. Based on actual requirements of a production unit, a mathematical model of grouping performance index, constraint conditions and decision variable was established and algorithm of best priority and variable neighborhood search was proposed for furnace grouping. There were three components of the algorithm, which included multi-layer quick sorting algorithm to determine furnace sequences, best priority and variable neighborhood search algorithm, and heuristic algorithm based on production rules for various grade of raw materials in stock. By using this algorithm for furnace grouping of 20 production work orders, sum of deviations of delivery time, product grade, and production priority was decreased from 58 to 42 with a reduction rate of 27.59% and satisfaction rate of raw material preparation was increased from 4 to 6 with an increase rate of 50%. Compared to results of manual furnace grouping for 40 production work orders, the furnace grouping results of this algorithm was reduced by 2 times of furnace usage. Further comparison with discrete particle swarm algorithm, acoustic variable neighborhood search algorithm, and adaptive variable neighborhood search algorithm demonstrated effectiveness of the proposed algorithm and validity of the mathematical model.

Key words: sintered NdFeB, furnace grouping, best priority, global optimization, manufacturing, model

中图分类号:

TP27

刘业峰, 柴天佑. 钕铁硼企业生产工单组炉的最佳优先和变邻域搜索算法[J]. 化工学报, 2018, 69(3): 1207-1214.

LIU Yefeng, CHAI Tianyou. The best priority and variable neighborhood search algorithm for production furnace grouping in NdFeB enterprises[J]. CIESC Journal, 2018, 69(3): 1207-1214.

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钕铁硼企业生产工单组炉的最佳优先和变邻域搜索算法

The best priority and variable neighborhood search algorithm for production furnace grouping in NdFeB enterprises

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