调度(生产过程)
自动化
院子
容器(类型理论)
作业车间调度
动态优先级调度
遗传算法
计算机科学
终端(电信)
分布式计算
整数规划
工程类
数学优化
运筹学
计算机网络
布线(电子设计自动化)
地铁列车时刻表
操作系统
运营管理
机械工程
物理
机器学习
量子力学
数学
算法
作者
Hui Li,Jianbiao Peng,Xi Wang,Jinlin Wan
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2021-12-01
卷期号:22 (12): 7607-7618
被引量:12
标识
DOI:10.1109/tits.2020.3005854
摘要
With the advancement of automation in transportation, the need to improve the operation efficiency of container terminals has increased. The most important determinant of container-handling efficiency is the productivity of equipment, such as quay cranes, automated lifting vehicles, storage yards, and yard cranes. Most previous studies have sought to optimize equipment assignments and scheduling independently and have considered only a loading or an unloading process. As loading and unloading processes occur simultaneously and the equipment operations are highly interrelated, it is important to direct the operations in an integrated manner that reflects the characteristics of automated container terminals. This paper presents a new mixed-integer programming model for analyzing the integrated problem of assigning resources and scheduling, which also considers the limited quantity of critical equipment. To solve the integrated optimization model, a genetic algorithm (GA) is developed. Since the critical equipment, such as yard cranes, are limited, and thus, restricting the efficiency of terminals, a sharing policy is proposed to improve the GA to shorten the operation time of both the loading and unloading processes. Experiments show that the improved GA proposed in this paper can obtain the optimal/near-optimal solutions in short CPU times, therefore it is efficient in solving the integrated equipment assignment and scheduling problem. The results obtained from the sharing policy are superior to those obtained from a non-sharing approach.
科研通智能强力驱动
Strongly Powered by AbleSci AI