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中国管理科学 ›› 2017, Vol. 25 ›› Issue (12): 126-137.doi: 10.16381/j.cnki.issn1003-207x.2017.12.014

• 论文 • 上一篇    下一篇

订单陆续到达下虚拟单元重调度驱动决策

韩文民1, 朱弢1, 李正义1, 翁红兵2, 蒋家尚3   

  1. 1. 江苏科技大学经济管理学院, 江苏 镇江 212003;
    2. 沪东中华造船集团有限公司, 上海 200129;
    3. 江苏科技大学数理学院, 江苏 镇江 212003
  • 收稿日期:2017-01-13 修回日期:2017-04-24 出版日期:2017-12-20 发布日期:2018-02-10
  • 通讯作者: 韩文民(1963-),男(汉族),江苏人,江苏科技大学经济管理学院,教授,博士生导师,研究方向:工业工程与管理.E-mail:wlmh63@163.com E-mail:wlmh63@163.com
  • 基金资助:

    国家自然科学基金资助项目(71271105);教育部人文社会科学研究规划基金项目(12YJA630036)

Rescheduling Driven Decision for Virtual Manufacturing Cellular under Sequential Orders Arriving

HAN Wen-min1, ZHU Tao1, LI Zheng-yi1, WENG Hong-bing2, JIANG Jia-shang3   

  1. 1. School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China;
    2. Hudong Zhonghua Shipbuilding Group Co., Ltd., Shanghai 200129, China;
    3. School of Mathematics and Physics, Jiangsu University of Science and Technology, Zhenjiang 212003, China
  • Received:2017-01-13 Revised:2017-04-24 Online:2017-12-20 Published:2018-02-10

摘要: 针对虚拟单元制造系统中新订单陆续到达的情形,研究了判断是否以及何时进行重调度的问题,即重调度驱动决策,以避免频繁的重调度。基于所提出的虚拟单元重调度非线性整数规划模型,结合混合离散粒子群算法,提出了新的基于损益的周期-事件混合重调度驱动决策方法。在每个重调度决策时刻,从时间的角度衡量了执行虚拟单元重调度方案将会产生的损失与收益,建立了损益函数,由此对重调度决策时刻进行判定和筛选,过滤掉不必要的重调度。最后,以船舶建造为例,验证了所提出的混合重调度驱动决策方法的可行性和有效性。实例表明,该方法能够在保证调度得到优化的同时,有效地减少重调度频率。

关键词: 虚拟单元, 重调度, 重调度驱动决策, 混合粒子群算法

Abstract: In the actual production environment, new orders arrive in succession. Usually, a new optimal scheduling plan is built every time a new order arrives, to make the production system runs more efficiently. As the scheduling plan changes too frequently, the "nervousness" of scheduling production has appeared. The control of the workshop is affected, and the stability of the production system is weakened. At present, studies on rescheduling problems mainly focus on the optimization of rescheduling method and the evaluation of rescheduling performance. The rescheduling driven decision-making has not gained enough attention.The rescheduling driven is a mechanism which determines when to reschedule.
The rescheduling driven in the virtual cellular manufacturing system is proposed, in order to reduce the times of rescheduling with new orders arriving continually, while keeping the high efficiency of the production system.
A new rescheduling driven decision-making method is propsed through the loss and gain of scheduling in virtual cellular manufacturing system. In this paper, loss and gain of scheduling is assessed from the perspective of time. The starting time deviations of tasks which exist in both the new scheduling plan and the old one are calculated, to measure the loss. Difference between the completion times before and after the rescheduling is considered as the profit of scheduling.
To ensure the optimization of rescheduling, a nonlinear 0-1 integer programming mathematical model with multi-objectives is established according to the characteristics of virtual cellular manufacturing system. Then a discrete particle swarm optimization algorithm with genetic operation is designed to solve the rescheduling model. Based on the rolling time horizon theory, the whole plan is divided into several periods by rescheduling points. Alternative rescheduling points are generated by a mixture of periodic and event strategy. At each point, the loss is compared with the gain of rescheduling based on the mathematical programming model, to find out whether it is appropriate to implement the rescheduling. If the gain can make up for the loss, the rescheduling will be carried out immediately; otherwise, this alternative time point will be canceled. With the proposed decision-making method, the reasonable rescheduling points are selected and the unnecessary ones are filtered out. As a result, the frequency of rescheduling is reduced.
The case of shipbuilding verifies that the proposed rescheduling driven decision-making method is feasible and efficient. The analysis of the case indicates that, compared to other driven strategies, this method can obviously decrease the rate of changing production plan without worsening scheduling performance index.

Key words: virtual cellular, reschedule, rescheduling driven decision, hybrid particle swarm algorithm

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