{"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}
引用次数: 8
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.