Dynamic route guidance algorithm based algorithm based on artificial immune system
Licai YANG
Jie LIN
Dewei WANG
Lei JIA
摘要：To improve the performance of the K-shortest paths search in intelligent traffic guidance systems,this paper proposes an optimal search algorithm based on the intelligent optimization search theory and the memphor mechanism of vertebrate immune systems.This algorithm,applied to the urban traffic network model established by the node-expanding method,can expediently realize K-shortest paths search in the urban traffic guidance systems.Because of the immune memory and global parallel search ability from artificial immune systems,K shortest paths can be found without any repeat,which indicates evidently the superiority of the algorithm to the conventional ones.Not only does it perform a better parallelism,the algorithm also prevents premature phenomenon that often occurs in genetic algorithms.Thus,it is especially suitable for real-time requirement of the traffic guidance system and other engineering optimal applications.A case study verifies the efficiency and the practicability of the algorithm aforementioned.
机标关键词：artificial immune systemshortest pathsguidance systemsgenetic algorithmssearch algorithmparallel searchnetwork modelimmune memory
分类号：TP3(计算技术、计算机技术)
资助基金：山东省自然科学基金(Y2005G12)国家自然科学基金(60674062)the Information Industry Foundation of Shandong Province(2006R00046)
论文发表日期：2007-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：6( 385-390 )
英文信息