Feed Formula Optimization Method Based on Multi-Objective Particle Swarm Optimization Algorithm

Ji-xin Zhang, Gao-ping Wang
{"title":"Feed Formula Optimization Method Based on Multi-Objective Particle Swarm Optimization Algorithm","authors":"Ji-xin Zhang, Gao-ping Wang","doi":"10.1109/IWISA.2010.5473663","DOIUrl":null,"url":null,"abstract":"In this paper, we set a multi-objective mathematical model for feed formula optimal problem, propose a new MOPSO-based feed formula optimal method. A global selection method of particle and a dominance-principle are presented. Simulation results show that the new algorithm can give us more satisfactory results and a set of solution. A new method for solving complicated problem about feed formula optimization is provided.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"891 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2010.5473663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In this paper, we set a multi-objective mathematical model for feed formula optimal problem, propose a new MOPSO-based feed formula optimal method. A global selection method of particle and a dominance-principle are presented. Simulation results show that the new algorithm can give us more satisfactory results and a set of solution. A new method for solving complicated problem about feed formula optimization is provided.
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
基于多目标粒子群算法的饲料配方优化方法
本文建立了饲料配方优化问题的多目标数学模型,提出了一种新的基于mopso的饲料配方优化方法。提出了粒子的全局选择方法和优势原则。仿真结果表明,新算法能给出较为满意的结果和一组解。为解决复杂的饲料配方优化问题提供了一种新的方法。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
How to Display the Data from Database by ListView on Android An Improved Genetic Algorithm and Its Blending Application with Neural Network A Study for Important Criteria of Feature Selection in Text Categorization A Hierarchical Classification Model Based on Granular Computing A Study of Improving Apriori Algorithm
×
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