Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism

The genetic algorithm can effectively handle some complex optimal problems that the conventional optimization methods can’t solve. However,the traditional genetic algorithm has many defects,such as falling easily into local solution,slower convergence speed and the poor effect of optimal problems wi...

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Main Authors: Ye Bin, Luo Jinliang
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2017-01-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.07.037
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author Ye Bin
Luo Jinliang
author_facet Ye Bin
Luo Jinliang
author_sort Ye Bin
collection DOAJ
description The genetic algorithm can effectively handle some complex optimal problems that the conventional optimization methods can’t solve. However,the traditional genetic algorithm has many defects,such as falling easily into local solution,slower convergence speed and the poor effect of optimal problems with constraints. An improved float-encoding genetic algorithm( FGA) solving optimal problems with inequality constraints is proposed. This method has the advantages of high convergence efficiency,good stability and strong local search capability. It is used to the optimal design of crank-link mechanism,and the optimal results show that the improved genetic algorithm has a better effect than the traditional genetic algorithm.
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spelling doaj.art-8fcb27cb952d4f95942f135e977636cf2023-05-26T09:45:21ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392017-01-014117617929931501Improved FGA and Its Applications in the Optimal Design of Four Bar MechanismYe BinLuo JinliangThe genetic algorithm can effectively handle some complex optimal problems that the conventional optimization methods can’t solve. However,the traditional genetic algorithm has many defects,such as falling easily into local solution,slower convergence speed and the poor effect of optimal problems with constraints. An improved float-encoding genetic algorithm( FGA) solving optimal problems with inequality constraints is proposed. This method has the advantages of high convergence efficiency,good stability and strong local search capability. It is used to the optimal design of crank-link mechanism,and the optimal results show that the improved genetic algorithm has a better effect than the traditional genetic algorithm.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.07.037Improved FGA algorithm;Crank-link mechanism;Inequality constraint;Optimal design
spellingShingle Ye Bin
Luo Jinliang
Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism
Jixie chuandong
Improved FGA algorithm;Crank-link mechanism;Inequality constraint;Optimal design
title Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism
title_full Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism
title_fullStr Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism
title_full_unstemmed Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism
title_short Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism
title_sort improved fga and its applications in the optimal design of four bar mechanism
topic Improved FGA algorithm;Crank-link mechanism;Inequality constraint;Optimal design
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.07.037
work_keys_str_mv AT yebin improvedfgaanditsapplicationsintheoptimaldesignoffourbarmechanism
AT luojinliang improvedfgaanditsapplicationsintheoptimaldesignoffourbarmechanism