New scheduling algorithms and digital tool for dynamic permutation flowshop with newly arrived order
针对新订单随机到达的动态排列流水车间调度问题，提出一种整合匹配策略与实时策略的新调度方法，并开发了包含十一种启发式算法的数字工具，经案例验证有效。
The permutation flowshop scheduling problem has been widely studied under static environment by assuming machines and jobs are available at the time of zero. However, in reality, new orders arrive at production systems randomly, which leads to sheer complexity in scheduling due to the dynamic changes given various constraints of resources. Previous studies simply attach new orders directly after the existing schedule. Recent study shows mixing jobs of old and new orders could result in better scheduling solutions. But the heuristic algorithms are still lacking to implement the job mixing policy. To address this problem, a novel scheduling strategy is herein proposed by integrating match-up strategy and real-time strategy (MR) in order to make use of the remaining time before the old order due date. Based on the new MR strategy, eleven new heuristics are introduced with ten existing and one new priority rules. Computational results illustrate the effectiveness of the new heuristics. A digital tool is developed for ease of application of these heuristics, and it is validated by case studies.