Please submit manuscripts in either of the following two submission systems

    ScholarOne Manuscripts

  • ScholarOne
  • 勤云稿件系统

  • 登录

Search by Issue

  • 2024 Vol.31
  • 2023 Vol.30
  • 2022 Vol.29
  • 2021 Vol.28
  • 2020 Vol.27
  • 2019 Vol.26
  • 2018 Vol.25
  • 2017 Vol.24
  • 2016 vol.23
  • 2015 vol.22
  • 2014 vol.21
  • 2013 vol.20
  • 2012 vol.19
  • 2011 vol.18
  • 2010 vol.17
  • 2009 vol.16
  • No.1
  • No.2

Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

期刊网站二维码
微信公众号二维码
Related citation:Xian-Min Wei.Research on Ant Colony Algorithm in Vehicle Operation Adjustment Based on IOT[J].Journal of Harbin Institute Of Technology(New Series),2013,20(2):17-21.DOI:10.11916/j.issn.1005-9113.2013.02.004.
【Print】   【HTML】   【PDF download】   View/Add Comment  Download reader   Close
←Previous|Next→ Back Issue    Advanced Search
This paper has been: browsed 1724times   downloaded 969times 本文二维码信息
码上扫一扫!
Shared by: Wechat More
Research on Ant Colony Algorithm in Vehicle Operation Adjustment Based on IOT
Author NameAffiliation
Xian-Min Wei Computer Engineering School, Weifang University, Weifang 261061, China 
Abstract:
Automatic solution of vehicle operation adjustment is the important content in realizing vehicle traffic command automation on Internet of Things platform. Based on both the organization realization of Internet of Things platform and the merging vehicle operation adjustment into the Flow-Shop scheduling problem in manufacturing systems, this paper has constructed the optimization model with a two-lane vehicle operation adjustment. With respect to the large model solution space and complex constraints, a better solution algorithm is proposed based on ant colony algorithm for optimal quick solution. The simulation results show that the algorithm is feasible and the approximate optimal solution can be quickly obtained.
Key words:  vehicles operation adjustment  flow-shop scheduling  optimization model  ant colony algorithm
DOI:10.11916/j.issn.1005-9113.2013.02.004
Clc Number:TN91
Fund:

LINKS