Collaborative optimization of layout and cutting scheduling for large-scale customized metal structural parts

Exploring the collaborative optimization mechanism of layout and cutting scheduling is a key scientific problem that enterprises must solve urgently. To balance the makespan, delay penalty, and sheet utilization rate for large scale customized metal structural parts, a two-stage model is proposed to cooperatively optimize the layout and cutting scheduling of rectangular metal structural parts, considering the processing characteristics. A layout model is established at the first stage to maximize the sheet utilization. Focusing on the sequence of sheet metal processing and machine selection, a mathematical model is formulated to minimize the makespan and delay penalty at the second stage. The layout problem at Stage 1 can be solved by the Improved Grey Wolf Optimizer (IGWO) algorithm. Based on the layout heuristic strategy, the parts with smaller priority values are laid first. The cutting scheduling problem (CSP) at Stage 2 is solved by the Modified Non-dominated Sorting Genetic Algorithm (MNSGA-II). The production scheduling heuristic strategy of the smaller priority values cutting first is formulated to generate the initial population. The experiment results show the effectiveness of the proposed two-stage model and the improved algorithms.