Abstract Manufacturing planning and control systems ideally seek to simultaneously achieve short and predictable flow times as well as high output and due-date performance. One approach to address this problem is the workload control concept. It is based on the idea to control lead times by controlling order releases and thus the level of work-in-process and output. The focus of this paper is on multi-period optimization models for order release planning. We use a simulation study of a make to order manufacturer in a rolling horizon setting and compare the performance of an order release model that assumes fixed lead times and a model that allows for variable lead times: An input output control and a clearing function model, respectively. We analyze two different approaches to cope with the varying and tight due date slack and find that including more foreknowledge of demand is preferable. Finally, we show that the clearing function model outperforms the input output control model in all scenarios by yielding lower inventory levels with shorter shop floor throughput times. This advantage seems not to be affected by the predictability of the demand, but the IOC model narrows the gap when using near optimal parameters especially for a scenario with deterministic demand.

中文翻译：

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具有固定和可变提前期的两种基于优化的订单发布模型的比较。

摘要 制造计划和控制系统理想地寻求同时实现短且可预测的流动时间以及高产出和到期日性能。解决此问题的一种方法是工作负载控制概念。它基于通过控制订单发布从而控制在制品和输出水平来控制提前期的想法。本文的重点是订单发布计划的多期优化模型。我们在滚动范围设置中使用按订单制造商的模拟研究，并比较假设提前期固定的订单发布模型和允许可变提前期的模型的性能：输入输出控制和清算功能模型，分别。我们分析了两种不同的方法来应对不断变化和紧迫的到期日余量，并发现包括更多的需求预知是可取的。最后，我们表明清算函数模型在所有场景中都优于输入输出控制模型，因为它以更短的车间吞吐量时间产生更低的库存水平。这种优势似乎不受需求可预测性的影响，但 IOC 模型在使用接近最优参数时缩小了差距，尤其是对于具有确定性需求的场景。