Intellectualization of a method for solving a logistics problem to optimize costs within the framework of Lean Production technology

E. Fedorov, P. Nikolyuk, Olga Nechporenko, Esta Chioma
{"title":"Intellectualization of a method for solving a logistics problem to optimize costs within the framework of Lean Production technology","authors":"E. Fedorov, P. Nikolyuk, Olga Nechporenko, Esta Chioma","doi":"10.46783/smart-scm/2020-3-1","DOIUrl":null,"url":null,"abstract":"In the article, within the framework of intellectualization of the Lean Production technology, it is proposed to optimize the costs arising from the insufficient efficiency of placing goods in the warehouse by creating an optimization method based on the immune metaheuristics of the T-cell model, which allows solving the knapsack constrained optimization problem. The proposed metaheuristic method does not require specifying the probability of mutation, the number of mutations, the number of selected new cells and allows using only binary potential solutions, which makes discrete optimization possible and reduces computational complexity by preventing permanent transformations of real potential solutions into intermediate binary ones and vice versa. An immune metaheuristic algorithm based on the T-cell model has been created, intended for implementation on the GPU using the CUDA parallel information processing technology. The proposed optimization method based on immune metaheuristics can be used to intellectualize the Lean Production technology. The prospects for further researches are to test the proposed methods on a wider set of test databases.","PeriodicalId":329393,"journal":{"name":"Electronic Scientific Journal Intellectualization of Logistics and Supply Chain Management #1 2020","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Scientific Journal Intellectualization of Logistics and Supply Chain Management #1 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46783/smart-scm/2020-3-1","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

In the article, within the framework of intellectualization of the Lean Production technology, it is proposed to optimize the costs arising from the insufficient efficiency of placing goods in the warehouse by creating an optimization method based on the immune metaheuristics of the T-cell model, which allows solving the knapsack constrained optimization problem. The proposed metaheuristic method does not require specifying the probability of mutation, the number of mutations, the number of selected new cells and allows using only binary potential solutions, which makes discrete optimization possible and reduces computational complexity by preventing permanent transformations of real potential solutions into intermediate binary ones and vice versa. An immune metaheuristic algorithm based on the T-cell model has been created, intended for implementation on the GPU using the CUDA parallel information processing technology. The proposed optimization method based on immune metaheuristics can be used to intellectualize the Lean Production technology. The prospects for further researches are to test the proposed methods on a wider set of test databases.
在精益生产技术框架内解决物流问题以优化成本的方法的智能化
本文在精益生产技术智能化的框架下,提出了一种基于t细胞模型的免疫元启发式优化方法,通过求解背包约束优化问题,来优化货物入库效率不足所产生的成本。提出的元启发式方法不需要指定突变的概率,突变的数量,选择的新细胞的数量,并且允许只使用二进制势解,这使得离散优化成为可能,并通过防止真实势解永久转换为中间二进制解来降低计算复杂性,反之亦然。提出了一种基于t细胞模型的免疫元启发式算法,并利用CUDA并行信息处理技术在GPU上实现。提出的基于免疫元启发式的优化方法可用于实现精益生产技术的智能化。进一步研究的前景是在更广泛的测试数据库上测试所提出的方法。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信