摘要
针对城市应急服务车辆(110、119、120等)的最优路径选择问题及路网的随机性与时变性,利用鲁棒优化理论,考虑路网在最坏情况下的行程时间,建立了随机时变条件下的应急车辆路径选择模型,并对Dijkstra算法进行改进,将算法的路阻矩阵进行实时更新,以在时变条件下实现对路径选择模型的求解。经算例分析表明,该模型能有效解决随机时变路网环境下的应急车辆最优路径问题,与基于概率分布的期望行程时间最短的方法相比,该模型拥有更高的鲁棒性和易操作性。
Concerning the optimal paths planning of urban emergency service vehicles（ such as 110, 119, 120, etc.）and stochastic time-dependent networks, using the robust optimization theory, the travel time of links in the worst case was considered and a route choice model in the stochastic time-dependent networks was proposed in this paper. The Dijkstra algorithm was improved with updating the impedance matrix in real time to solve this choice model under time-dependent networks. The experimental results indicate that this model can effectively solve the optimal paths planning problem of emergency vehicles in stochastic time-dependent networks. Compared with the method of searching the route of which expected travel time is the shortest based on distribution estimation, this method has higher robustness and feasibility.
出处
《计算机应用》
CSCD
北大核心
2014年第A02期317-319,共3页
journal of Computer Applications
基金
国家自然科学基金青年科学基金资助项目(71001079)
关键词
应急车辆
随机时变路网
鲁棒优化
最优路径
emergency vehicle stochastic time-dependent network robust optimization optimal path
