Overlap Detection in 2D Amorphous Shapes for Paper Optimization in Digital Printing Presses

Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures.

Automated summary

Paper waste from regular, irregular, and amorphous patterns is a critical issue in digital printing presses, impacting production costs directly. An iterated local search algorithm with a novel neighborhood structure efficiently solves the problem by detecting and correcting overlaps between different shapes.