Performance analysis and capacity planning for stochastic systems with cut-off service levels

具有截止服务水平的随机系统的性能分析和容量规划

• 批准号: 394845127
• 负责人: Professor Dr.-Ing. Kai Furmans
• 金额: --
• 依托单位: Institut für Fördertechnik und Logistiksysteme (IFL)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/394845127?language=en
• 关键词: Performance; analysis; capacity; planning; stochastic

The research project described in the renewal proposal is intended to investigate the influence of different cut-off service level definitions on capacity planning, in particular on workforce requirement planning and shift scheduling. These service level definitions are commonly used in industry. They define a cut-off time and a deadline by which all orders received by the cut-off time have to be completely processed. The structural differences in the definition of a cut-off service level compared to traditional service levels prevents the transfer of insights with regard to optimal capacities. Therefore, new methods for capacity planning have to be developed. The overall objective is therefore to identify and explain the influences of system parameters, e.g. the processing capacity available, on the achievable cut-off service level. This enables insights into the effects of cut-off service levels on workforce requirements and shift scheduling. For this purpose, performance analysis methods for stochastic, time-dependent, single-stage and multi-stage systems are to be developed. Discrete-time queueing networks will be used for the performance analysis. For appropriate special cases, structural insights are to be derived analytically. They are derived for deterministic surrogate models and single-period stochastic models. We develop new approaches for workforce requirement planning and shift scheduling by using a cut-off service level. The structural findings gained before will serve as bounds in the solution approaches. The single stage results will then be extended to multi-level systems, based on the results of the current project.

更新建议中所述的研究项目旨在调查不同的截止服务水平定义对能力规划的影响，特别是对劳动力需求规划和轮班安排的影响。这些服务级别定义通常用于工业中。它们定义了一个截止时间和一个截止日期，在截止时间之前收到的所有订单都必须被完全处理。与传统服务水平相比，在界定截止服务水平方面存在结构性差异，这妨碍了对最佳能力的深入了解。因此，必须开发新的能力规划方法。因此，总的目标是确定和解释系统参数的影响，例如可用的处理能力，对可实现的截止服务水平。这使我们能够深入了解截止服务水平对劳动力需求和轮班安排的影响。为此目的，性能分析方法的随机，时间依赖性，单级和多级系统的发展。将使用离散时间神经网络进行性能分析。对于适当的特殊情况，结构的见解是通过分析得出的。它们是针对确定性代理模型和单周期随机模型而导出的。我们开发了新的方法，劳动力需求规划和轮班安排使用截止服务水平。以前获得的结构发现将作为解决方案的界限。然后，将根据当前项目的结果，将单阶段的结果扩展到多层次的系统。