The distributed flow shop scheduling problem with inter-factory transportation
研究了多个工厂间运输中间品对流水车间调度的影响，提出一种迭代贪婪搜索算法来最小化总完工时间，发现运输能缓解瓶颈、提高设备利用率。
Large manufacturing companies often manage a network of multiple factories, creating a distributed flow shop scheduling problem for flowline manufacturing processes. This problem involves assigning jobs to one of several distributed factories, each equipped with identical flow shops, and completing the jobs within their designated factory. We expand upon the traditional distributed flow shop scheduling problem by incorporating the transportation of intermediate goods between factories. This transportation can occur after each machine, with shipping times dependent on the distance between the origin and destination factories, potentially delaying further processing. Our objective is to minimize the makespan across all factories. We introduce an iterated greedy search procedure specifically designed for distributed flow shop scheduling with inter-factory transportation. Based on a graph representation, a speed-up procedure is developed to improve the algorithms search ability. Through computational studies, we demonstrate the effectiveness and efficiency of our proposed algorithm, and provide insights into the benefits of transportation. Our findings indicate that incorporating transportation enhances machine utilization across factories by alleviating bottlenecks, ultimately improving overall efficiency and reducing makespan. Besides, we are able to quantify the trade-off between transport times and the benefits of inter-factory transportation. • Extension of distributed flow shop scheduling by inter-factory transportation. • Development of mathematical and constraint programming formulations. • Iterated greedy search with speed-up approach based on graph representation. • Results show that transportation improves resource utilization and reduces makespan.