Multiple routes planning based on particle swarm algorithm and hierarchical clustering

De Yun Zhou, Xiao Yang Li, Kun Zhang, Qian Pan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This paper presents a multiple routes planning algorithm based on particle swarm algorithm (PSO) and hierarchical clustering to overcome the problem of the sensitivity of k-means clustering to the initial clustering center. Firstly, numerous feasible routes are initialed by PSO. Secondly, the model of multiple routes planning based on hierarchical clustering algorithm is designed and the hierarchical clustering is used to divide the initial feasible routes into several categories. Finally, the PSO algorithm is used to find the optimal route of each category, and then the route smooth algorithm is used to get the final optimal route. Simulation results demonstrate the effectiveness of the routes cluster by hierarchical clustering and the feasibility of the algorithm.

Original languageEnglish
Title of host publicationProceedings of the 34th Chinese Control Conference, CCC 2015
EditorsQianchuan Zhao, Shirong Liu
PublisherIEEE Computer Society
Pages42-46
Number of pages5
ISBN (Electronic)9789881563897
DOIs
StatePublished - 11 Sep 2015
Event34th Chinese Control Conference, CCC 2015 - Hangzhou, China
Duration: 28 Jul 201530 Jul 2015

Publication series

NameChinese Control Conference, CCC
Volume2015-September
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference34th Chinese Control Conference, CCC 2015
Country/TerritoryChina
CityHangzhou
Period28/07/1530/07/15

Keywords

  • hierarchical clustering
  • multiple routes planning
  • particle swarm algorithm (PSO)

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