化工学报 ›› 2018, Vol. 69 ›› Issue (3): 913-922.DOI: 10.11949/j.issn.0438-1157.20171406

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基于状态设备网络的改进间歇生产调度模型

闫雪丽, 韩豫鑫, 顾幸生   

  1. 华东理工大学化工过程先进控制与优化技术教育部重点实验室, 上海 200237
  • 收稿日期:2017-10-24 修回日期:2017-11-12 出版日期:2018-03-05 发布日期:2018-03-05
  • 通讯作者: 顾幸生
  • 基金资助:

    国家自然科学基金项目(61573144,61673175)。

Improved schedule model for batch production by state unit network

YAN Xueli, HAN Yuxin, GU Xingsheng   

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • Received:2017-10-24 Revised:2017-11-12 Online:2018-03-05 Published:2018-03-05
  • Supported by:

    supported by the National Natural Science Foundation of China (61573144, 61673175).

摘要:

建立有效的间歇生产调度模型一直是生产调度问题研究的热点,基于特定事件点的连续时间建模方法是优化短期间歇生产调度问题的有效工具。基于状态设备网络和特定事件点概念,建立非线性的连续时间间歇生产调度模型。为了解决非线性引起的求解困难,该模型使用替代方法线性化模型中的双线性项,替代法不仅将建立的混合整数非线性规划模型转化为混合整数线性规划模型,且由于其不包含大M松弛项,能使模型搜索空间更紧凑,模型求解效率更高。通过3个实例对比实验表明了基于状态设备网络描述的改进间歇生产调度模型搜索高效性。另外,模型中还给出了不同存储条件下,基于状态设备网络描述的间歇生产调度模型约束,扩展了模型适用性。

关键词: 间歇调度问题, 生产, 模型, 状态设备网络, 优化

Abstract:

Establishing effective model for scheduling batch process has always been a hot spot of production planning research. Continuous-time model based on unit-specific-event is evolved as a promising tool for optimizing short-term schedule of batch process. A nonlinear programming model for contiguous batch production was developed on the basis of state unit network and specific event time point. To overcome challenges of solving nonlinear model, a replacement technique was used so that non-linear items in the model were linearized. Consequently, the nonlinear mixed integral program model became a linear one. Because of no big M relaxation item, the linear mixed integral model had compact search space and improved solving efficiency. The simulation results of three batch processes illustrated excellent efficiency and stability of the new model. Furthermore, constraints of the new model at different storage states were provided to expand model applicability.

Key words: batch processes scheduling, production, model, state unit network, optimization

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