Advancement of the automatic simplification of discrete event material flow models by using continuous model elements.

通过使用连续模型元素，推进离散事件物料流模型的自动简化。

• 批准号: 210226088
• 负责人: Dr. Daniel Huber
• 金额: --
• 依托单位: School of Computing, Informatics, and Decision Systems Engineering
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2011
• 资助国家: 德国
• 起止时间: 2010-12-31 至 2012-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/210226088?language=en
• 关键词: Advancement; automatic; simplification; discrete; event

Models in material flow simulation are of growing size and detail. Because of the increased complexity the simulation runtime is too big for conducting experiments in an efficient manner. One possibility to improve runtime is reducing the model complexity by using model simplification. The price of model simplification however is the creation of behavioral deviation in relation to the original model. A method of model simplification which takes complexity and behavioral deviation into account was developed by the applicant in his dissertation. The developed method simplifies models automatically and controls the complexity and behavioral deviation in order to create models of specific properties.This method shall be significantly improved and extended in this research project. The achievable complexity reduction shall be increased and the deviation shall be reduced when complexity is constant. This goal is to be reached by using hybrid simulation. The simplified discrete event model is coupled with continuous models. These continuous models are representing those model components of the original model on an abstract level which were substituted during simplification. By using hybrid simulation, components get substitutable which were not substitutable previously and the dynamics of substituted components is better approximated. Additionally, a function shall be developed, which calculates changes in the sequence of jobs based on the states of the discrete and the continuous models as they occur in the original model caused by overtaking and priority rules. All methods shall be developed in a matter, such that they are applicable by an algorithm for automatic simplification and are to be implemented prototypical and are thoroughly evaluated.

物流模拟中的模型规模越来越大，细节越来越多。由于复杂性的增加，模拟运行时太大，无法以有效的方式进行实验。改进运行时的一种可能性是通过使用模型简化来降低模型复杂性。然而，模型简化的代价是创建与原始模型相关的行为偏差。申请人在论文中提出了一种考虑复杂性和行为偏差的模型简化方法。该方法自动简化模型，控制模型的复杂性和行为偏差，以建立具有特定性质的模型，该方法将在本研究项目中得到显著的改进和推广。当复杂度不变时，应增加可实现的复杂度降低，并减少偏差。这一目标可以通过使用混合模拟来实现。简化的离散事件模型与连续模型耦合。这些连续模型在抽象级别上表示原始模型的那些在简化过程中被替换的模型组件。通过混合仿真，可以得到以前不可替代的部件，并能更好地逼近被替代部件的动态特性。此外，还应开发一个函数，该函数根据离散模型和连续模型在原始模型中因超车和优先级规则而发生的状态，计算作业顺序的变化。所有方法应在一个问题中开发，以使它们可通过自动简化的算法来应用，并应实现原型并进行彻底评估。