A Unified Decomposition Matheuristic for Assembly, Production, and Inventory Routing
针对装配路径规划问题，提出一种三阶段分解元启发式算法，同时优化生产、库存和供应商物料收集的车辆路径，在大量标准测试实例上取得781个新最优解。
While the joint optimization of production and outbound distribution decisions in a manufacturing context have been intensively studied in the past decade, the integration of production, inventory, and inbound transportation from suppliers have received much less attention despite its practical relevance. This paper aims to fill the gap by introducing a general model for the assembly routing problem (ARP), which consists of simultaneously planning the assembly of a finished product at a plant and the routing of vehicles collecting materials from suppliers to meet the inventory requirements imposed by the production. We formulate the problem as a mixed-integer linear program and we propose a three-phase decomposition matheuristic that relies on the iterative solution of different subproblems. The first phase determines a setup schedule while the second phase optimizes production quantities, supplier visit schedules and shipment quantities. The third phase solves a vehicle routing problem for each period in the planning horizon. The algorithm is flexible, and we show how it can also be used to solve two well-known outbound distribution problems related to the ARP: the production routing problem and the inventory routing problem. Using the same parameter setting for all problems and instances, we obtain 781 new best-known solutions out of 2,628 standard IRP and PRP test instances. In particular, on large-scale multivehicle instances, the new algorithm outperforms specialized state-of-the-art heuristics for these two problems. The online appendix is available at https://doi.org/10.1287/ijoc.2018.0817 .