基于群智能算法的自动化码头协同调度研究

Integrated scheduling of automated container terminal based on swarm intelligence algorithm

为了提高码头作业效率和服务水平,保障港口在激烈竞争中的生存和发展,研究自动化码头自动引导车、岸桥和自动化轨道吊的协同调度问题。根据边装边卸作业模式,建立混合整数规划模型,以完成船舶装卸时间最小化为目标,利用群智能算法中多种算法进行求解。通过数值实验证明了该模型的有效性,获得优化的调度方案,并对不同算法的性能进行比较。结果表明启发式的混合遗传粒子群算法能够在最短的时间内获得最优解,其在求解的质量和速度方面都表现得更为优秀,可以应用于码头的实际作业中。

To improve the working efficiency and service level of terminals,this paper studied the integrated scheduling problem of the automated guided vehicle,gantry cranes and automated rail-mounted gantry in automated terminals,which could make sure ports to survive and develop in the fierce competition. According to the loading and unloading operation mode,it built the mixed integer programming model with the goal of minimizing the ship loading and unloading time,and through various algorithms of swarm intelligence to solve this problem. It proved the effectiveness of this model,and obtained optimized scheduling scheme by numerical experiments,it compared the different performance of algorithms. The results show that the HGA-PSO algorithm can get the optimal solution in the shortest time,the quality and speed of this solution are excellent,which can be applied to the practical operation of terminals.