Journal of South China University of Technology(Natural Science) >

2011 , Vol. 39 >Issue 8: 109 - 112,117

DOI: https://doi.org/10.3969/j.issn.1000-565X.2011.08.020

Traffic & Transportation Engineering

Improved Particle Swarm Optimization Algorithm of Ergodic Model for Routing Planning of Delivery Vehicle Navigation

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  • 1. School of Highway,Chang’an University,Xi’an 710064,Shaanxi,China; 2. Guangdong Provincial Highway Administration,Guangzhou 510075,Guangdong,China; 3. School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,Guangdong,China
章权(1963-) ，男，博士生，现任广东省公路管理局高级工程师，主要从事交通运输规划与管理、公路桥梁勘察、设计、公路管理等研究．

Received date: 2010-12-17

  Revised date: 2011-06-16

  Online published: 2011-07-06

Supported by

国家自然科学基金资助项目( 50978106)

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Abstract

Vehicle routing planning is known as the key link in the logistics delivery vehicle navigation system as well as the precondition for the logistics delivery routing guidance and the technical support for vehicle navigation. In order to solve the routing planning problem,an ergodic model is established for Vehicle Routing Planning of Navigation in Logistics Distribution ( VND) ,and an improved particle swarm optimization algorithm is proposed to
solve the model. Then,the generation method of the initial population and the evolutionary strategy of the population are improved to work out the PSO algorithm which originally can not be directly used to solve the VND problem,thus achieving good results in solving the VND problem. Case studies show that the algorithm is of fast computing capability and preferable convergence.

Key words： delivery vehicle navigation; routing planning; ergodic model; particle swarm optimization algorithm; population evolution

Cite this article

Zhang Quan Wen Hui-ying Sun Bo . Improved Particle Swarm Optimization Algorithm of Ergodic Model for Routing Planning of Delivery Vehicle Navigation[J]. Journal of South China University of Technology(Natural Science), 2011 , 39(8) : 109 -112,117 . DOI: 10.3969/j.issn.1000-565X.2011.08.020

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