When directly extracting tool line data from digital die-cutting,there will be resulting in the problem of empty tool paths being too long.In this study,an improved path planning method based on genetic algorithm was proposed to address the disorder in the order of die-cutting.Firstly,the characteristics of the knife line file data were analyzed,and the starting points of each element's die-cutting were decomposed into chromosomes composed of element numbers and initial die-cutting point numbers within each element.The chromosomes were divided into head and tail for separate transformation processing.Among them,genetic and crossover transformations were carried out to address the uniqueness of the element number,while genetic and mutation transformations were carried out to address the fact that the initial die-cutting point whose number cannot be greater than the total number of die-cutting points in the element.In order to improved efficiency and avoided local optimization,this algorithm first optimized the order of primitives through a one-dimensional optimization method,the result of the optimization was used as the initial chromosome sequence,and then the genetic algorithm was used for further optimization.By comparing this algorithm with the direct path planning algorithm for tool line die-cutting through example calculation,the results showed that the optimized empty path length of the die-cutting path is much smaller than the empty path length in direct path planning.It means that this algorithm save running time,and greatly improve the efficiency of digital die-cutting.
Digital die-cuttingPath planningGenetic algorithm optimization
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