Abstract: There are many uncertainties in the operation of automated container terminals, which largely affect the efficiency of the terminals. Therefore, it is extremely vital to study the collaborative scheduling of equipment resources in automated container terminals under uncertainties. At the same time, fully automated container terminals have been newly built in recent years or based on the original terminal equipment for automation transformation, which is bound to have a mix of old and new equipment, so how to make the new and old equipment to work well together to improve the efficiency of the terminal is also within the scope of our study.
Although large ports around the world are currently dispatched unmanned, there is still room for improvement in overall dispatching efficiency. After a research on Xiamen YH automated container terminal,considering the business logic and equipment characteristics of the automated container terminal, we propose the mixed process operation mode on the basis of a single loading and unloading process, which is better applicable to the modified automated container terminal. The mixed process studied in this paper is a combination of five types of loading and unloading equipment: double-trolley shore bridge, single-trolley shore bridge, AGV, collector truck and yard bridge, i.e., double-trolley shore bridge and single-trolley shore bridge act on one ship at the same time, and two types of horizontal transportation equipment, AGV and collector truck, are put in place. It is dynamic for the operating environment of container terminals and there are uncertainties such as uncertainty of vessel arrival time, machinery own failure, fluctuation of loading and unloading efficiency and other uncontrollable factors, which cannot be accurately predicted by these parameters. When historical data can meet the needs of reality, uncertainty can be represented by probability distribution, etc.; when historical data cannot meet the needs of reality, fuzziness can better describe the uncertain variables existing in the terminal. In this study, the three uncertain factors are considered: demand of horizontal transportation equipment, travel time and operation time of vertical loading and unloading equipment in the scheduling problem. And aimed at minimizing the maximum completion time,a multi-equipment resources cooperative scheduling optimization model of shore bridge, horizontal transportation equipment and yard bridge are established, and the Beetle swarm algorithm is introduced.
The YH automated container terminal data is used as an example for empirical evidence, the Beetle whisker search algorithm and Beetle swarm. The results show that the Tenebrae swarm algorithm designed in this paper is more convergent and the quality of the solutions obtained is better. Taking the uncertainty factors into account is closer to the practical terminal operation environment, and considering the hybrid process is more applicable to the utilization of existing equipment resources in the process of terminal automation transformation. The proposed model considering uncertain factors and hybrid processes and the Tenno swarm algorithm are an effective method to study the collaborative scheduling of equipment resources in automated container terminals.

Key words: automated container terminal, Beetle swarm algorithm, uncertain factors, mixed process, collaborative scheduling

摘要： 本文提出了一种基于混合工艺的自动化集装箱码头设备资源协同调度优化模型。针对自动化集装箱码头的业务逻辑和设备特性,将单一装卸工艺扩展为混合工艺作业模式,以更好地适用于改建的自动化集装箱码头。考虑了调度问题中水平运输设备的需求量、行驶时间和垂直装卸设备的运作时间三个不确定性因素,以最大完工时最小化为目标,建立岸桥、水平运输设备、场桥多设备资源协同调度优化模型,并引入天牛群算法进行求解。通过对YH自动化集装箱码头数据的实证分析,结果表明:本文提出的模型和天牛群算法是一种研究自动化集装箱码头设备资源协同调度的有效方法。

关键词: 自动化集装箱码头, 天牛群算法, 不确定性因素, 混合工艺, 协同调度