面向集装箱装船排箱优化调度问题的交互感知狼群算法

An interactive perception wolf pack algorithm for shipping order optimization of containers

在海运市场迅速发展,港口竞争日益激烈的背景下,进一步提高港口资源利用效率和调度智能化,提升港口作业效率尤为重要。集装箱装卸船作业是港口生产的主要工作内容之一。针对港口集装箱装船排箱优化调度问题,提出一种适于解决该问题的交互感知狼群算法。首先,以最优化堆场及船舶装卸集装箱翻箱量为目标,参照相关研究建立了便于应用群智能算法的装船排箱问题模型。其次,利用狼群算法具有等级分工的交互环节,面向问题改进了召唤、奔袭、围攻环节,提出一种自适应调整的交互策略改进狼群算法。最后,针对问题模型设计了多种工况并与其他算法进行比较,证明了交互感知狼群算法在此问题上的有效性与实用性。

In the context of the rapid development of the shipping market and increasingly fierce port competition,it is particularly important to further improve port resource utilization efficiency and dispatch intelligence,and enhance port operation efficiency.Container loading and unloading operations are one of the main tasks of port production.Aiming at the optimal scheduling problem of port container loading and packing,an interactive perception wolf pack algorithm suitable for solving this problem is proposed.Firstly,with the goal of optimizing the yard and the amount of container tipping in the loading and unloading of ships,a model of loading and arranging containers that is convenient for applying swarm intelligence algorithms is established by referring to related research.Secondly,we use the hierarchical interaction of wolf colony algorithm to improve such issues as summoning,attacking and sieging,and propose an adaptive interaction strategy to improve the wolf colony algorithm.Finally,a variety of working conditions are designed for the problem model and compared with other algorithms to prove the effectiveness and practicability of the interactive perception wolf pack algorithm.