To cater to the growing personalized need of customers, increasingly more make-to-order distribution centers consider a two-phase production (i.e. raw material granulation and order packaging) process when making production and routing decisions, especially for time-sensitive commodities. In this article, we extend the production routing problem to the make-pack-route problem (MPRP) to devise production and routing schedules that allow for flexible order composition and ensure in-time delivery. To solve the MPRP, we propose an iterative sequential scheduling heuristic embedded with the local search, which sequentially solves the three corresponding scheduling problems and improves the overall schedule in an iterative manner. Our numerical studies verify that our method can solve practically meaningful instances (e.g. up to 200 orders and 30 items) in an acceptable time duration (i.e. 1 hour). Our studies show an average 11.6% reduction in the total processing cost compared to an ad hoc scheduling method commonly used in practice. Our studies also suggest that our solution method saves more costs with more orders, higher order variety and larger average commodity quantity and variety in each order.

为了满足客户日益增长的个性化需求，越来越多的按订单生产的配送中心在制定生产和工艺路线决策时，尤其是对时间敏感的商品，会考虑两阶段生产（即原料制粒和订单包装）过程。在本文中，我们将生产工艺路线问题扩展到制造包工艺路线问题（MPRP），以设计生产和工艺路线计划，以实现灵活的订单组合并确保及时交货。为了解决MPRP，我们提出了一种嵌入本地搜索的迭代顺序调度启发式算法，该算法顺序解决了三个相应的调度问题，并以迭代方式改进了整体调度。我们的数值研究证明，我们的方法可以解决实际有意义的实例（例如 最多200个订单和30个项目）在可接受的持续时间（即1小时）内。我们的研究表明，与实际使用的临时计划方法相比，总处理成本平均降低了11.6％。我们的研究还表明，我们的解决方案可以节省更多成本，更多的订单，更高的订单品种以及每个订单中更大的平均商品数量和品种。