求解MNW随机用户均衡问题的改进人工鱼群算法
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摘要
MNW随机用户均衡模型解决了Logit模型所有路径感知方差完全相等的假设,因此在交通分配中具有一定的应用前景。针对这一模型,本文采用了一种定向搜索变异的改进人工鱼群算法,该算法在迭代时可以保证鱼群在当前状态下自适应变异的同时还可以向当前的最佳位置移动。随后在固定需求下的Nguyen&Dupuis中对该算法进行验证,取得了预期的结果,说明了MNW模型良好的应用价值。同时,针对实验中存在的不足提出了进一步的研究方向。
MNW Stochastic User Equilibrium model relaxes the assumption that all route perception variances of Logit model are equal,so it has a certain application prospect in traffic assignment. This paper adopts an improved Artificial Fish Swarm algorithm based on directed search variation to solve the MNW Stochastic User Equilibrium model. This algorithm can guarantee the adaptive mutation of fish swarm in the current state and move to the optimal position at the same time in the iteration. The performances are verified through an experiment with fixed demand in Nguyen & Dupuis network,and the expected results showthat MNW model is applicable in practice. Based on the above,considering the shortcomings of the experiment,the paper points out a direction of the further research.
MNW Stochastic User Equilibrium model relaxes the assumption that all route perception variances of Logit model are equal,so it has a certain application prospect in traffic assignment. This paper adopts an improved Artificial Fish Swarm algorithm based on directed search variation to solve the MNW Stochastic User Equilibrium model. This algorithm can guarantee the adaptive mutation of fish swarm in the current state and move to the optimal position at the same time in the iteration. The performances are verified through an experiment with fixed demand in Nguyen & Dupuis network,and the expected results showthat MNW model is applicable in practice. Based on the above,considering the shortcomings of the experiment,the paper points out a direction of the further research.
引文
[1]WARDROP J G. Some theoretical aspects of road traffic research[J]. Proceeding of the Institute of Civil Engineers,1956,1(2):57-68.
[2] DAGANZO C F,SHEFFI Y. On stochastic models of traffic assignment[J]. Transportation Science,1977,11(3):253-274.
[3]黄海军.城市交通网络平衡分析:理论与实践[M].北京:人民交通出版社,1994.
[4] CASTILLO E,MENENDEZ J M,JIMNEZ P,et al. Closed form expressions for choice probabilities in the Weibull case[J].Transportation Research Part B:M ethodological,2008,42(4):373-380.
[5] KITTHAMKESORN S,CHEN A. A path-size weibit stochastic user equilibrium model[J]. Transportation Research Part B:M ethodological,2013,57:378-397.
[6]刘炳全,孙广才.基于Logit分配的交通网络设计模型的改进粒子群算法[J].科学技术与工程,2008,8(19):5446-5450,5456.
[7]张福龙.基于最大最小蚁群算法的随机用户交通分配模型研究[D].西安:长安大学,2016.
[8]刘建美,马帅奇.关于求解随机用户均衡问题的截断拟牛顿型信赖域法研究[J].数学的实践与认识,2017,47(10):184-190.
[9]魏秋月.基于蚁群优化的随机用户均衡模型研究[D].西安:长安大学,2017.
[10]姜山,季业飞.改进的人工鱼群混合算法在交通分配中的应用[J].计算机仿真,2011,28(6):326-329.
[2] DAGANZO C F,SHEFFI Y. On stochastic models of traffic assignment[J]. Transportation Science,1977,11(3):253-274.
[3]黄海军.城市交通网络平衡分析:理论与实践[M].北京:人民交通出版社,1994.
[4] CASTILLO E,MENENDEZ J M,JIMNEZ P,et al. Closed form expressions for choice probabilities in the Weibull case[J].Transportation Research Part B:M ethodological,2008,42(4):373-380.
[5] KITTHAMKESORN S,CHEN A. A path-size weibit stochastic user equilibrium model[J]. Transportation Research Part B:M ethodological,2013,57:378-397.
[6]刘炳全,孙广才.基于Logit分配的交通网络设计模型的改进粒子群算法[J].科学技术与工程,2008,8(19):5446-5450,5456.
[7]张福龙.基于最大最小蚁群算法的随机用户交通分配模型研究[D].西安:长安大学,2016.
[8]刘建美,马帅奇.关于求解随机用户均衡问题的截断拟牛顿型信赖域法研究[J].数学的实践与认识,2017,47(10):184-190.
[9]魏秋月.基于蚁群优化的随机用户均衡模型研究[D].西安:长安大学,2017.
[10]姜山,季业飞.改进的人工鱼群混合算法在交通分配中的应用[J].计算机仿真,2011,28(6):326-329.