考虑运输能力限制的跨单元调度方法

刘兆赫; 李冬妮; 王乐衡; 田云娜

doi:10.16383/j.aas.2015.c140498

考虑运输能力限制的跨单元调度方法

doi: 10.16383/j.aas.2015.c140498

1.
北京理工大学计算机学院智能信息技术北京市重点实验室北京 100081;
2.
延安大学数学与计算机科学学院延安 716000

基金项目:

国家自然科学基金(71401014),北京市自然科学基金(4122069)资助

详细信息

作者简介:
刘兆赫北京理工大学计算机学院硕士研究生. 主要研究方向为演化计算和生产调度. E-mail: cyuyan888@163.com

通讯作者:
李冬妮北京理工大学计算机学院副教授. 主要研究方向为智能优化, 企业计算,物流管理. E-mail: ldn@bit.edu.cn

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出版历程
- 收稿日期: 2014-07-21
- 修回日期: 2014-12-04
- 刊出日期: 2015-05-20

An Inter-cell Scheduling Approach Considering Transportation Capacity Constraints

1.
Beijing Key Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081;
2.
College of Mathematics and Computer Science, Yan'an University, Yan'an 716000

Funds:

Supported by National Natural Science Foundation of China (71401014), and Beijing Natural Science Foundation (4122069)

摘要

摘要: 工件在生产单元之间频繁转移产生了跨单元调度问题.本文结合我国装备制造业的生产实际,提出考虑运输能力的跨单元调度方法,设计了一种基于离散蜂群与决策块结构的超启发式算法.针对传统超启发式算法的局限性提出动态决策块策略, 同时改进传统蜂群算法的侦查蜂策略,使之具有更好的优化性能.实验表明,动态决策块具有比静态决策块更好的性能,算法在优化能力和计算效率的综合性能上优势显著,并且问题的规模越大,优势越明显.
- 跨单元调度 /
- 运输能力 /
- 超启发式 /
- 决策块 /
- 人工蜂群算法
Abstract: The issue of inter-cell scheduling arises due to some exceptional parts having to be processed and transported frequently in different cells. This work is inspired by the equipment manufacturing industry of China. Aimed at the inter-cell scheduling problem with transportation capacity constraints, a hyper-heuristic based on discrete artificial bee colony approach and decision block is proposed, in which a dynamic decision block strategy is developed and the scout bee strategy is improved. Experimental results show that the proposed approach outperforms the traditional static decision block strategies, and has a better performance with respect to the overall performance of optimization capability and computation efficiency, which is especially more suitable for large dimension scheduling problems.
- Inter-cell scheduling /
- transportation capacity /
- hyper-heuristic /
- decision block /
- artiˉcial bee colony algorithm

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参考文献(19)

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