摘要
为了制定合理的集装箱码头泊位岸桥资源调度计划,提高码头作业效率和客户满意度,基于离散泊位布局,建立了以在港集装箱船总的服务成本最小为优化目标的动态泊位岸桥协调调度模型。设计了遗传算法对模型求解,通过将部分约束条件嵌入算法结构简化了模型求解难度,并对算法迭代过程中的不可行解采用逐时刻基因调整策略进行修复。经过若干算例的数值实验,验证了模型和算法的可行性和有效性。
A reasonable allocation of port resources in container terminals can improve the efficiency of terminal operation and customer satisfaction. To achieve this goal, an integrated dynamic berth and quay-crane scheduling model which aims at minimizing the total service cost of vessels is proposed based on discrete berth layout. Then an improved genetic algorithm is presented to solve this model. Some constraint conditions of the model are embedded in the structure of this algorithm to reduce the model-solving difficulty. And infeasible solutions generated in the iterative process are repaired by using moment-to-moment gene-adjustment strategy. At last, the effectiveness and efficiency of the proposed model and algorithm are testified by several test instances.
出处
《计算机工程与应用》
CSCD
北大核心
2018年第3期265-270,共6页
Computer Engineering and Applications
基金
辽宁省自然科学基金(No.2015020033)
关键词
离散泊位
动态协调调度
遗传算法
集装箱码头
discrete berth layout
integrated dynamic scheduling
genetic algorithm
container terminal