A Genetic Algorithm for the Nesting Problem With Continuous Rotations

被引：0
|
作者：
Nunes, Wesley H. B. [1 ]
Moreira, Mayron C. O. [1 ]
Andretta, Marina [2 ]
机构：
[1] Univ Fed Lavras, Dept Ciencia Comptacao, Lavras, Brazil
[2] Univ Sao Paulo, Dept Matemat Aplicada & Estat, Sao Carlos, SP, Brazil
来源：
2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021) | 2021年
基金：
巴西圣保罗研究基金会;
关键词：
Nesting; Continuous Rotation; Heuristics;
D O I：
10.1109/CEC45853.2021.9504813
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The Nesting problem, or the irregular cutting and packing problem, aims to find the best position of irregular pieces within a board, minimizing the space used by them. The problem's relevance is that it is widely used in the furniture, textile, and footwear industries. We consider a two-dimensional scope with convex and non-convex parts, with continuous rotation. We implement a genetic algorithm that uses five positioning rules, five sorting rules, and two rotation rules to create individuals and populations. Two positioning rules outperformed the others, obtaining promising results compared with the literature.
引用
收藏
页码：1107 / 1114
页数：8
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