摘要
研究交通拥堵的有效调度问题,提高调度的效率。针对传统的车辆调度算法在进行车辆调度路径选择时,需要建立一定的预估性约束条件,一旦建立一个的约束条件受阻,会影响其它约束条件的生效,造成算法收敛速度慢、易陷于局部最优、车辆拥堵时调度效率较低的问题。为了解决上述问题,提出使用优先适合启发式算法与人工鱼群算法相结合的混合人工鱼群算法求解拥堵时车辆的高效调度问题,运用鱼群中的觅食、群聚等数学模型,解决约束冲突弊端,进行最优调度路径的准确定位仿真。实验结果表明,混合人工鱼群算法能快速有效的求解车辆拥堵问题,解决了最优调度路径的选择,为求解车辆高效调度提供了参考,具有广阔的应用前景。
To improve the efficiency of traffic congestion effective scheduling, the paper propsed a congestion sol- ving algorithm which combines priority heuristic algorithm with artificial fish swarm algorithm to solve the efficient ve- hicles scheduling problem. It used the mathematical models of foraging, clustering to complete the accurate positio- ning of optimal scheduling path. The experimental results show that the hybrid artificial fish swarm algorithm can rap- idly and efficiently solve traffic congestion.
出处
《计算机仿真》
CSCD
北大核心
2012年第6期328-331,共4页
Computer Simulation
关键词
车辆调度
人工鱼群
调度效率
Vehicle scheduling
Artificial fish swarm algorithm
Scheduling efficiency
