Aiming at the general integrated scheduling problem of tree-structured complex single-product machining and assembling, a reverse order hierarchical integrated scheduling algorithm (ROHISA) is proposed by considering the dynamic time urgency degree (TUD) of process sequences (PSs). The strategy of process sorting is put forward, and the TUD of PS is defined. The process tree is reversed using leaf alignment, and according to the order from leaf to root, the scheduling order of leaf nodes in the same layer is determined layer by layer according to the TUD values of the PSs to which the leaf nodes belong. In turn, the sorted leaf nodes in each layer are stored in a corresponding layered array (LA). Finally, the elements in each LA are reversed, and the LAs’ arranging order is reversed. A reverse order hierarchical scheduling strategy is proposed. Starting from the root node, every LA is taken as a unit to conduct trial scheduling each time. Under the condition of meeting the craft constraints, a set of quasi-scheduling schemes of same-layer processes (QSS_SLP) is obtained, and the one with the minimum end time is selected from it as the scheduling scheme of the same layer processes (SS_SLP). If it is not unique, the QSS_SLP that machines all the same layer processes (SLP) as early as possible is selected. The research shows that the ROHISA optimizes the integrated scheduling results of single-product manufacturing enterprises and improves its production efficiency.

In order to effectively allocate processes of Aa single complex product to two workshops with the same equipment, an integrated scheduling algorithm of two workshops based on process end time driven and processing area priority is proposed. To optimize the total processing time, a process scheduling strategy based on process end time driven is proposed. By scheduling multiple devices at the same time, the parallelism of process execution is improved, in order to reduce the total processing time and improve the utilization rate of equipment. In order to optimize the process migration times between two workshops, a workshop assignment strategy based on process processing area priority is proposed, which comprehensively considers the influence of the immediate preceding process, neighbor process and friend process of the schedulable process on workshop assignment and makes the process in the same processing area be processed in the same workshop as much as possible, so as to reduce the process migration times. The example analysis shows that the proposed algorithm is superior to the existing two workshops integrated scheduling algorithms in terms of reducing the total processing time, reducing the process migration times, and improving the utilization rate of equipment.

The integrated scheduling problem is a classical combinatorial optimization problem. The existing integrated scheduling algorithms generally adopt the short-time scheduling strategy that does not fully consider the impact of the degree of process parallelism on scheduling results. In order to further optimize the total processing time of a product and the utilization rate of a device, an integrated scheduling algorithm based on a process end time-driven and the long-time scheduling strategy is proposed. The proposed integrated scheduling algorithm sets up a separate candidate process queue for each device and determines the scheduling order for each scheduling queue on the premise of satisfying the constraint conditions of the process tree. Driven by the process end time, the algorithm finds schedulable processes for each device. If the schedulable process is unique, it is scheduled. Otherwise, if the schedulable process is not unique, the process with long-path and long-time is scheduled. In particular, the scheduling strategies of the scheduling queues of different devices are symmetric, and the constraint relationships between the processes in different queues are asymmetric. The case analysis results show that the proposed integrated scheduling algorithm is better than some existing algorithms in terms of the total processing time of a product and the average utilization rate of devices. Therefore, the proposed algorithm provides a new idea for processing the scheduling of a single complex product.