集卡动态调度路径优化算法

从整体调度的角度出发,分析了整个码头作业面的动态调度方案,提出了一种新的集装箱卡车(集卡)动态调度路径的自适应蚁群算法。运用码头GPRS系统,以集卡速度、流量、位置等相关数据建立了感知链。通过判断阻塞状况和调整可行点集,确定了信息素浓度更新策略与转移概率计算方法。针对码头路网的复杂性和蚁群算法的实时计算效率,设计了蚁群算法的步骤。将信息熵引入到蚁群算法中,运用MATLAB软件,对集卡的动态调度方案进行了仿真计算。计算结果表明:当初始集卡速度分别为50、75km.h-1,初始集卡流量分别为800、1 000veh.h-1时,集卡行驶的最短路径为4.3km,行驶时间为0.057h;集卡行驶的最优路径为8.3km,行驶时间为0.111h。可见,该算法能有效缓解码头阻塞问题,提高集卡利用率和码头作业效率。

Path optimization algorithm of dynamic scheduling for container truck

From the point of integrated scheduling,the dynamic scheduling method of whole terminal operating field was analyzed,and a new adaptive ant colony optimization of dynamic scheduling for container truck was put out.The GPRS system of terminal was used,and the perception chain was set up by using related data such as the speed,flow and position of container truck.Through judging obstruction status and adjusting feasible point set,the calculation methods of updating strategy and transition probability for pheromone concentration were determined.Aiming at the complexity of terminal road network and the real-time calculation efficiency of ant colony optimization,the steps of ant colony optimization were designed.The information entropy was introduced into ant colony optimization,the MATLAB software was used,and the simulation calculation of dynamic scheduling method for container truck was carried out.Simulation result shows that when the initial speeds of container trucks are 50,75 km·h-1 respectively and the initial flows of container trucks are 800,1 000 veh·h-1 respectively,the shortest driving path of container truck is 4.3 km,and the driving time is 0.057 h.The optimal driving path of container truck is 8.3 km,and the driving time is 0.111 h.By using the proposed algorithm,the obstruction problem of terminal can be remitted effectively,and the utilization ratio of container truck and the operating efficiency of terminal can increase obviously.3 tabs,2 figs,16 refs.