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Milp-based Campaign Scheduling In A Specialty Chemicals Plant: A Case Study

机译:特殊化工厂中基于Milp的活动计划:一个案例研究

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Supply chain management in chemical process industry focuses on production planning and scheduling to reduce production cost and inventories and simultaneously increase the utilization of production capacities and the service level. These objectives and the specific characteristics of chemical production processes result in complex planning problems. To handle this complexity, advanced planning systems (APS) are implemented and often enhanced by tailor-made optimization algorithms. In this article, we focus on a real-world problem of production planning arising from a specialty chemicals plant. Formulations for finished products comprise several production and refinement processes which result in all types of material flows. Most processes cannot be operated on only one multi-purpose facility, but on a choice of different facilities. Due to sequence dependencies, several batches of identical processes are grouped together to form production campaigns. We describe a method for multicriteria optimization of short- and mid-term production campaign scheduling which is based on a time-continuous MILP formulation. In a preparatory step, deterministic algorithms calculate the structures of the formulations and solve the bills of material for each primary demand. The facility selection for each production campaign is done in a first MILP step. Optimized campaign scheduling is performed in a second step, which again is based on MILP. We show how this method can be successfully adapted to compute optimized schedules even for problem instances of real-world size, and we furthermore outline implementation issues including integration with an APS.
机译:化工行业的供应链管理侧重于生产计划和调度,以降低生产成本和库存,同时提高生产能力的利用率和服务水平。这些目标和化学生产过程的特定特征导致复杂的计划问题。为了处理这种复杂性,高级计划系统(APS)得以实施,并且通常通过量身定制的优化算法进行增强。在本文中,我们重点讨论特种化学品工厂引起的生产计划的实际问题。制成品的配方包括多个生产和提炼过程,导致所有类型的物料流。大多数过程不能仅在一个多功能设备上运行,而只能在不同的设备上运行。由于顺序的依赖性,将几批相同的过程分组在一起以形成生产活动。我们描述了一种基于时间连续的MILP公式的短期和中期生产活动计划的多标准优化方法。在准备步骤中,确定性算法将计算配方的结构并解决每个主要需求的物料清单。在第一步MILP中完成每个生产活动的设施选择。在第二步中执行优化的活动计划,这也是基于MILP的。我们展示了该方法如何成功地适用于即使对于实际大小的问题实例也可以计算优化的计划表,此外,我们还概述了实现问题,包括与APS的集成。

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