.png){kind=icon}
返回
Fast pattern-based algorithms for cutting stock
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cor.2014.03.003.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The conventional assignment-based first/best fit decreasing algorithms (FFD/BFD) are not polynomial in the one-dimensional cutting stock input size in its most common format. Therefore, even for small instances with large demands, it is difficult to compute FFD/BFD solutions. We present pattern-based methods that overcome the main problems of conventional heuristics in cutting stock problems by representing the solution in a much more compact format Using our pattern-based heuristics, FFD/BFD solutions for extremely large cutting stock instances, with billions of items, can be found in a very short amount of time. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
Cutting stock
First fit decreasing
Best fit decreasing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.3
论文数:
6.5K
被引数:
1.8W
机构
.png){kind=icon}
