陈艳运用了蚁群算法作为最优路径选择算法，并设计了相应的路径选择模块，以

陈艳运用了蚁群算法作为最优路径选择算法，并设计了相应的路径选择模块，以路段距离作为路段权值，路径距离最短为目标[10]。景玲采用了遗传算法实现了最优路径求解，并以路段长度作为权值[11]。王荣彦也采用了遗传算法作为最优路径选择算法，不同的是，其构建了动态路段行驶时间函数模型求出路段行驶时间，并将其作为路网权值[12]。杨志勇、赵凛、张星臣等学者研究了先验信息下的出行者路径选择模型，而该模型研究了先验信息前提下的路径选择，而不是出行者获得实时信息的情况[13]。张赫、杨兆生、王炜等人运用增量加载的方法确定最优路径，利用预测的路段交通流量按比例分解成K部分，每一部分利用BPR函数计算路段行程时间，运用Dijkstra算法确定最短路[14]。

結果 (英文) 1:

Chen yan using Ant Colony optimization algorithm for optimal path selection algorithm, and designing the routing module, with road distances as road weight, path is the shortest distance to the target [10]. Jing Ling optimal path planning using genetic algorithm and using road length as weights [11]. Wang Rongyan also uses a genetic algorithm for optimal path selection algorithm, difference is, which builds dynamic link travel time function link travel time model obtained, and used as weights of road network [12]. Yang Zhiyong, Linda Zhao, Zhang Xingchen scholars study traveler's route choice model under the prior information, and the premise of route choice model prior information, rather than the traveler access to real-time information in [13]. Jang hyuk, Yang Zhaosheng, Wang Wei, who use method to determine the optimal path for incremental loads, with forecast traffic flows proportionally divided into k parts, each part with BPR function calculates the travel time, using the Dijkstra algorithm to determine shortest path [14].

結果 (英文) 2:

Chen Yan used the ant colony algorithm as the optimal path selection algorithm and design the corresponding routing modules to road distance as the road weights, the shortest path distance for the target [10]. Jing Ling uses a genetic algorithm to solve the optimal path, and link length as the weights [11]. Wang Rongyan also used genetic algorithms as the optimal path selection algorithm is different is that it constructs a dynamic link travel time model to obtain road travel time, and as the road network weights [12]. Yang Zhiyong, Zhao cold, 张星臣 other scholars who studied the travel route choice model under a priori information, and the model to study the path selection prior information under the premise, not the travelers to get real-time information of the case [13]. Zhang He, Yangzhao Sheng, Wang Wei, who use the method to determine the optimal path incremental load using the predicted road traffic proportionally decomposed into K parts, each using the BPR function calculates travel time, using Dijkstra algorithm to determine the shortest path [14 ].

結果 (英文) 3:

Chen Yan use of the ant colony algorithm is the choice of the optimal path algorithm, and design the corresponding path selection module, to link distance as the road weight, shortest path to the target [10]. Jing Ling adopts genetic algorithm to realize the optimal path problem, and in section length as the weight of [11]. Wang Rongyan also uses genetic algorithm as the optimal path selection algorithm, different is, it constructs the dynamic link travel time function model to calculate the travel time, and take it as the network weight [12]. Yang Zhiyong, Zhao Lin, Zhang Xingchen and other scholars have studied the prior information of the travelers' route choice model,While the model to study the path of prior information under the premise of choice, rather than the traveler to obtain real-time information of [13]. Zhang He, Yang Zhaosheng, Wang Wei, et al. Method by using the incremental loading and determine the optimal path, according to the proportion of decomposed into K section using the road traffic flow prediction, each part using the BPR function to calculate the link travel time, the use of Dijkstra algorithm to determine the shortest path [14].