装配序列规划的混合DPSO-SA方法

HongGuang Lv, Cong Lu, Jun Zha
{"title":"装配序列规划的混合DPSO-SA方法","authors":"HongGuang Lv, Cong Lu, Jun Zha","doi":"10.1109/ICMA.2010.5589203","DOIUrl":null,"url":null,"abstract":"In this paper, an assembly sequence planning (ASP) approach is proposed with a multi-objective hybrid evolutionary search algorithm, which combines a discrete particle swarm optimization (DPSO) algorithm and a simulated annealing (SA) algorithm. Based on a special assembly sequence coding method and corresponding update strategy, the effects caused by the changes of parameters in the hybrid DPSO and SA (DPSO-SA) algorithm are investigated, and the performance of the proposed DPSO-SA algorithm is compared with the existing DPSO algorithm. Case study shows that the hybrid DPSO-SA approach can be more efficient to generate optimal assembly sequences, and can significantly increase the search capability and perform better than the DPSO algorithm.","PeriodicalId":145608,"journal":{"name":"2010 IEEE International Conference on Mechatronics and Automation","volume":"439 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A hybrid DPSO-SA approach to assembly sequence planning\",\"authors\":\"HongGuang Lv, Cong Lu, Jun Zha\",\"doi\":\"10.1109/ICMA.2010.5589203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an assembly sequence planning (ASP) approach is proposed with a multi-objective hybrid evolutionary search algorithm, which combines a discrete particle swarm optimization (DPSO) algorithm and a simulated annealing (SA) algorithm. Based on a special assembly sequence coding method and corresponding update strategy, the effects caused by the changes of parameters in the hybrid DPSO and SA (DPSO-SA) algorithm are investigated, and the performance of the proposed DPSO-SA algorithm is compared with the existing DPSO algorithm. Case study shows that the hybrid DPSO-SA approach can be more efficient to generate optimal assembly sequences, and can significantly increase the search capability and perform better than the DPSO algorithm.\",\"PeriodicalId\":145608,\"journal\":{\"name\":\"2010 IEEE International Conference on Mechatronics and Automation\",\"volume\":\"439 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Mechatronics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2010.5589203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2010.5589203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

提出了一种结合离散粒子群优化(DPSO)算法和模拟退火(SA)算法的多目标混合进化搜索算法的装配序列规划(ASP)方法。基于一种特殊的装配序列编码方法和相应的更新策略,研究了DPSO-SA混合算法(DPSO-SA)中参数变化对装配序列编码的影响,并将所提出的DPSO-SA算法与现有DPSO算法的性能进行了比较。实例研究表明,混合DPSO- sa方法能更有效地生成最优装配序列,显著提高了搜索能力,性能优于DPSO算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid DPSO-SA approach to assembly sequence planning
In this paper, an assembly sequence planning (ASP) approach is proposed with a multi-objective hybrid evolutionary search algorithm, which combines a discrete particle swarm optimization (DPSO) algorithm and a simulated annealing (SA) algorithm. Based on a special assembly sequence coding method and corresponding update strategy, the effects caused by the changes of parameters in the hybrid DPSO and SA (DPSO-SA) algorithm are investigated, and the performance of the proposed DPSO-SA algorithm is compared with the existing DPSO algorithm. Case study shows that the hybrid DPSO-SA approach can be more efficient to generate optimal assembly sequences, and can significantly increase the search capability and perform better than the DPSO algorithm.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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