摘要
为了研究交通网络耗时最优路径选择问题,建立了随机网络环境下自适应最可靠路径问题的数学模型。首先,建立随机网络模型反映交通网络的耗时随机特性;其次,在该网络环境下定义最可靠路径策略和最可靠状态链,并且证明最可靠状态链满足动态规划的Bellman's准则;第三,构造基于动态规划的逐次逼近算法求解该问题,并且证明提出的逐次逼近算法是多项式时间算法;最后,编写基于MATLAB计算机语言的算法程序,并针对实际交通网络Sioux Falls(SF)network展开数值试验,计算结果验证了该算法的正确性和可行性。
In order to analyze the problem of selecting optimal path in traffic network,adaptive reliable shortest path problem is addressed in stochastic network.First,the mathematical model of stochastic traffic network is established to reflect the stochastic characteristic of traffic time in traffic network.Second,the optimal-reliable routing policy and optimal-reliable state chain based on reliability theory are uniformly defined in stochastic network;and the optimal-reliable state chain satisfies Bellman＇s principle that is the core of dynamic programming.Third,a successive approximation algorithm based on the dynamic programming is developed to solve the adaptive reliable shortest path problem in stochastic network,whose complexity is polynomial time.Finally,a computer program using Matlab language is developed to compute on the SiouxFalls（SF）network.Numerical results in typical transportation network show the validity and feasibility of the successive approximation algorithm.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2014年第6期1622-1627,共6页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金重点项目(U1134206)
国家自然科学基金外青学者项目(51250110075
51050110143)
交通运输部西部项目(0901005C)
江苏省自然科学基金创新学者攀登计划项目(SBK200910046)
美国国家科学基金总统奖项目(CMMI-0408390)
美国国家科学基金项目(CMMI-0644552)
关键词
智能交通
随机网络
可靠性
动态规划
最短路
intelligent transportation stochastic network reliability dynamic programming shortest path
