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:LIU Yun-zhong.A novel genetic algorithm for vehicle routing problem with time windows[J].Journal of Harbin Institute Of Technology(New Series),2010,17(3):437-444.DOI:10.11916/j.issn.1005-9113.2010.03.028.
【Print】   【HTML】   【PDF download】   View/Add Comment  Download reader   Close
←Previous|Next→ Back Issue    Advanced Search
This paper has been: browsed 695times   downloaded 604times 本文二维码信息
码上扫一扫!
Shared by: Wechat More
A novel genetic algorithm for vehicle routing problem with time windows
Author NameAffiliation
LIU Yun-zhong Statistic School,Xi’an University of Finance and Economics,Xi’an 710100,China 
Abstract:
A novel genetic algorithm with multiple species in dynamic region is proposed,each of which occupies a dynamic region determined by the weight vector of a fuzzy adaptive Hamming neural network. Through learning and classification of genetic individuals in the evolutionary procedure,the neural network distributes multiple species into different regions of the search space. Furthermore,the neural network dynamically expands each search region or establishes new region for good offspring individuals to continuously keep the diversification of the genetic population. As a result,the premature problem inherent in genetic algorithm is alleviated and better tradeoff between the ability of exploration and exploitation can be obtained. The experimental results on the vehicle routing problem with time windows also show the good performance of the proposed genetic algorithm.
Key words:  genetic algorithm  multiple species  neural network  premature problem  vehicle routing problem with time windows
DOI:10.11916/j.issn.1005-9113.2010.03.028
Clc Number:TP18
Fund:

LINKS