Evolutionary-based hybrid algorithm for 2D cutting stock problem

M. Fathy, M. Osama, M. El-Mahallawy
{"title":"Evolutionary-based hybrid algorithm for 2D cutting stock problem","authors":"M. Fathy, M. Osama, M. El-Mahallawy","doi":"10.1109/INTELCIS.2015.7397260","DOIUrl":null,"url":null,"abstract":"Cutting stock problem (CSP) affects cost of production and stock use efficiency in many industries. The majority of such industries handle stock of raw material in sheet form with the priority of waste reduction. Thus, in this paper we study the two-dimensional CSP (2-D CSP) with main goal of minimizing trim loss. Current approaches are primarily designed to deal with regular stock sheets only and do not handle irregular or defective sheets. That is why the problem is considered to be partially solved from an industrial stand point. In this paper, we introduce a novel algorithm for 2D CSP to minimize the waste and address the issue of defective and/or irregular stock sheets. The algorithm utilizes image processing, evolutionary-programming (EP), and Linear programming (LP) to form a practical solution. Detection & Isolation of sheets' defects and conversion of irregular sheets to regular is accomplished by image processing. Further processing is done by the remaining techniques to efficiently minimize the waste. Experimental results show that the proposed algorithm succeeds in achieving lower waste values compared to conventional EP algorithms.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELCIS.2015.7397260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Cutting stock problem (CSP) affects cost of production and stock use efficiency in many industries. The majority of such industries handle stock of raw material in sheet form with the priority of waste reduction. Thus, in this paper we study the two-dimensional CSP (2-D CSP) with main goal of minimizing trim loss. Current approaches are primarily designed to deal with regular stock sheets only and do not handle irregular or defective sheets. That is why the problem is considered to be partially solved from an industrial stand point. In this paper, we introduce a novel algorithm for 2D CSP to minimize the waste and address the issue of defective and/or irregular stock sheets. The algorithm utilizes image processing, evolutionary-programming (EP), and Linear programming (LP) to form a practical solution. Detection & Isolation of sheets' defects and conversion of irregular sheets to regular is accomplished by image processing. Further processing is done by the remaining techniques to efficiently minimize the waste. Experimental results show that the proposed algorithm succeeds in achieving lower waste values compared to conventional EP algorithms.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
二维切料问题的进化混合算法
切削库存问题影响着许多行业的生产成本和库存利用效率。大多数这类工业处理以单张形式储存的原材料,优先考虑减少浪费。因此,在本文中,我们研究二维CSP (2-D CSP)的主要目标是最小化修剪损失。目前的方法主要是设计来处理正常的库存单,而不处理不规则或有缺陷的单。这就是为什么从工业的角度来看,这个问题被认为部分解决了。在本文中,我们介绍了一种新的二维CSP算法,以最大限度地减少浪费,并解决不良和/或不规则库存单的问题。该算法利用图像处理、进化规划(EP)和线性规划(LP)来形成一个实用的解决方案。通过图像处理实现板材缺陷的检测与隔离,将不规则板材转化为规则板材。进一步的处理由剩余的技术来完成,以有效地减少浪费。实验结果表明,与传统的EP算法相比,该算法可以获得更低的浪费值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
On the use of probabilistic model-checking for the verification of prognostics applications Prospective, knowledge based clinical risk analysis: The OPT-model Partial deduction in predicate calculus as a tool for artificial intelligence problem complexity decreasing XML summarization: A survey Finding the pin in the haystack: A Bot Traceback service for public clouds
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1