基于人机交互-蚁群算法的港口疏船调度优化

摘要

To solve the ship dredging scheduling problem of many ships detained caused by port unable to work normally,this paper considers the interests of both the ship and the port,and is focused on a multi-objective optimization model with the objectives of shortest average time at port,lowest additional operation cost and fastest recovery to normal order of production.Multi-attribute utility theory is adopted to transform the multi-objective to a single objective optimization and construct the evaluation function.This paper selects improved ant colony algorithm combined with human-computer interaction and neighborhood search for optimization.The actual case in Dalian container terminal is used for verification.The result shows that the model could solve the ship dredging scheduling problem better than the original schedule.Moreover,the improved algorithm has a higher efficiency than conventional ant colony algorithm.The proposed model and algorithm can provide a new thought and approach for production organization in the container terminal.%为解决因港口无法正常作业导致大量船舶压港后的疏船调度问题,从同时兼顾船公司和港口方利益出发,建立了船舶平均在港时间最短、额外作业成本最低、生产秩序恢复最快的调度生产多目标优化模型.利用多属性效用理论将多目标转换为单目标,并构建了相应的评价函数,采用改进的蚁群算法并结合人机交互以及邻域搜索方法求解,最后以大连港集装箱码头实际案例进行验证.结果表明,与通常调度方法相比,文中建立的优化模型能够更好地解决疏船问题;对比常规的蚁群算法,改进后的算法搜索效率更高.上述模型和算法为集装箱码头的生产组织调度提供了新的优化思路和方法.