Flexible integrated scheduling algorithm based on remaining work probability selection coding

Abstract

Aiming at the integrated scheduling problem of tree-structured products with flexible machine selection, this article proposes a flexible integrated scheduling algorithm based on remaining work probability selection coding. The algorithm is based on the framework of a genetic algorithm. First, in order to ensure the diversity and goodness of the initial population, an encoding method based on remaining work probability selection is proposed. Second, two new different crossover and mutation methods are designed based on operation and position respectively, which ensure the legitimacy of the generated offspring individuals. Then, in order to enhance the searchability of the algorithm for an optimal solution of the problem, a local search strategy based on the machine is proposed. Finally, a simple and effective decoding method based on the idle period is given. The algorithm is tested by the existing instance and randomly generated instances. The experimental results show that the proposed algorithm's solving speed and solution quality outperform other comparison algorithms.

A Flexible Integrated Scheduling Algorithm for Dynamic Determination Processing Equipment Considering the Root-Subtree Vertical and Horizontal Pre-Scheduling

“…This section reviews the related works on the flexible integrated scheduling algorithms, aiming to solve the flexible integrated scheduling problem better. A new algorithm for complex product flexible scheduling with constraint between jobs (FISA-CPFS) in literature [10] uses a distributed method to select the processing equipment for the process according to the shortest time-consuming strategy, and then uses the quasi-critical path method to determine the processing sequence of the processes; The algorithm in literature [13] uses the equipment driving moment to determine the process equipment according to the shortest processing time, and combines the substantial short-path strategy to find the combination scheme that ends as soon as possible to determine the final processing equipment and processing sequence; Dynamic parallel integrated flexible scheduling algorithm based on device driver and essential path (FISA-DDEP) in literature [14] adopts the idle device driving strategy and the dynamic substantial path strategy to determine the processing equipment and the processing sequence of the parallel process, and realize the substantial parallel processing between the processes; Flexible integrated scheduling algorithm based on reverse order layer priority (FISA-ROLP) in literature [15] uses the reverse order layer priority strategy and the dynamic quasilength path strategy to determine the scheduling order of the process, and uses the equipment selection strategy and the device preemption strategy to determine the processing equipment of the target process; The literature [16,17] proposed an intelligent algorithm based on the genetic algorithm framework to solve the flexible integrated scheduling problem. These algorithms are simply based on the vertical or horizontal strategy of the process tree to determine the process scheduling sequence, which cannot achieve both vertical and horizontal, and rely too much on the product structure attributes.…”

A Two-Workshop Collaborative, Integrated Scheduling Algorithm considering the Prescheduling of the Root-Subtree Processes

“…is effectively utilizes idle resources and reduces production costs. At present, the integrated scheduling in single-workshop production has been deeply studied in the general, integrated scheduling, the special constraint relationship, and the flexible equipment [11][12][13][14][15], which is gradually developing in the direction of two workshops or multiworkshops distributed manufacturing [16] according to the actual production demand. As the production fields involved in the integrated scheduling become increasingly extensive, the distributed integrated scheduling for two-workshop collaborative production in the same or different enterprises with the same processing equipment resources has become the research focus.…”

A Reverse Order Hierarchical Integrated Scheduling Algorithm Considering Dynamic Time Urgency Degree of the Process Sequences

“…From the analysis of machining equipment attributes, the integrated scheduling problem is divided into flexible workshop scheduling [12][13][14] and non-flexible workshop scheduling.…”