基于改进模拟植物生长算法的集装箱码头插船调度优化

摘要

为解决临时接受计划外船舶到港作业的插船调度问题，建立了综合考虑港口安排插船作业的成本最小优化模型，将模拟植物生长算法（PGSA）改进后进行求解。经过对实际案例进行计算分析后表明，所建模型和算法可以有效解决上述问题并取得了较好结果。为验证算法的有效性，同时引入遗传算法进行计算对比，结果显示经改进的 PGSA在求解过程中具有较好的收敛速度与精确度。采用本文建立的模型和算法能够快速解决临时插船的调度调整问题，为集装箱码头在特殊情况下泊位调度优化提供了解决问题的思路和方法。%In order to solve the berth scheduling problem of unexpected arrived vessels,this paper models an optimization model which aims to minimum cost of arranging the operations of unexpected arrived vessels from the port’s view and solves it by an improved plant growth simulation algorithm (PGSA ).The analysis of an actual case shows that the model and algorithm can effectively solve the above problems and achieve good results. Genetic algorithm is also included in this paper to compare with improved PGSA,the results show that improved PGSA has better speed and precision,thus more effective.The model and algorithm in this paper will solve the berth scheduling problem of unexpected arrived vessels more effectively and provide ideas and methods in container terminal under special conditions.