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Optimization of extended business processes in digital supply chains using mathematical programming
Computers & Chemical Engineering ( IF 4.3 ) Pub Date : 2021-04-28 , DOI: 10.1016/j.compchemeng.2021.107323
Hector D. Perez , Satyajith Amaran , Esra Erisen , John M. Wassick , Ignacio E. Grossmann

We propose a mathematical programming approach to optimize the business process transactions in digital supply chains. Five scheduling models from the Process Systems Engineering (PSE) area are applied to schedule the processing of orders in a simplified Order-To-Cash (OTC) business process, which is modeled as a multistage network with parallel units (agents). Two case studies are presented to compare the performance of the scheduling models on various sizes of a flexible jobshop representation of the OTC process. The models are compared and scaled to select those that are more suitable to this application. The continuous-time general precedence model provides an accurate representation of the real system and performs well for small instances. The discrete-time State-Task Network (STN), however, proves most efficient in terms of tractability, despite the well-known limitations resulting from discretizing time. The tightness of the linear programming (LP) relaxations in the discrete-time STN framework, as well as the ability of commercial solvers to perform preprocessing and apply heuristics to the STN formulation, enables finding near optimal solutions quickly even for larger instances.



中文翻译:

使用数学规划优化数字供应链中的扩展业务流程

我们提出了一种数学编程方法来优化数字供应链中的业务流程交易。流程系统工程 (PSE) 领域的五个调度模型用于在简化的订单到现金 (OTC) 业务流程中调度订单处理,该流程被建模为具有并行单元(代理)的多级网络。提供了两个案例研究来比较调度模型在不同规模的 OTC 流程的灵活作业车间表示上的性能。对模型进行比较和缩放,以选择更适合此应用程序的模型。连续时间一般优先模型提供了真实系统的准确表示,并且在小实例中表现良好。然而,离散时间状态任务网络 (STN) 在易处理性方面被证明是最有效的,尽管时间离散会带来众所周知的限制。离散时间 STN 框架中线性规划 (LP) 松弛的紧密性,以及商业求解器执行预处理并将启发式应用于 STN 公式的能力,即使对于较大的实例也能快速找到接近最优的解决方案。

更新日期:2021-06-14
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