Version 1
: Received: 21 October 2021 / Approved: 22 October 2021 / Online: 22 October 2021 (15:41:54 CEST)
How to cite:
Martinez-Martinez, G.; Sanchez-Romero, J.; Jimeno-Morenilla, A.; Mora-Mora, H. An Improved Nesting Algorithm for Irregular Patterns. Preprints2021, 2021100334. https://doi.org/10.20944/preprints202110.0334.v1
Martinez-Martinez, G.; Sanchez-Romero, J.; Jimeno-Morenilla, A.; Mora-Mora, H. An Improved Nesting Algorithm for Irregular Patterns. Preprints 2021, 2021100334. https://doi.org/10.20944/preprints202110.0334.v1
Martinez-Martinez, G.; Sanchez-Romero, J.; Jimeno-Morenilla, A.; Mora-Mora, H. An Improved Nesting Algorithm for Irregular Patterns. Preprints2021, 2021100334. https://doi.org/10.20944/preprints202110.0334.v1
APA Style
Martinez-Martinez, G., Sanchez-Romero, J., Jimeno-Morenilla, A., & Mora-Mora, H. (2021). An Improved Nesting Algorithm for Irregular Patterns. Preprints. https://doi.org/10.20944/preprints202110.0334.v1
Chicago/Turabian Style
Martinez-Martinez, G., Antonio Jimeno-Morenilla and Higinio Mora-Mora. 2021 "An Improved Nesting Algorithm for Irregular Patterns" Preprints. https://doi.org/10.20944/preprints202110.0334.v1
Abstract
In industrial environments, nesting consists in cutting or extracting pieces from a material sheet, with the purpose of minimizing the surface of the sheet used. This problem is present in different types of industries, such as shipping, aeronautics, woodworking, footwear, and so on. In this work, the aim is to find an acceptable solution to solve complex nesting problems. The research developed is oriented to sacrifice accuracy for speed so as to obtain robust solutions in less computational time. To achieve this, a greedy method and a genetic algorithm have been implemented, being the latter responsible for generating a sequence for the placement of the pieces, where each piece is placed in its current optimal position with the help of a representation system for both the pieces and the material sheet.
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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