Integrated Scheduling of Different Types of Handling Equipment at Automated Container Terminals

Effective control and operation of handling equipment in port container terminals are crucial in enhancing the overall efficiency and performance of container handling in import, export and transshipment. Nowadays, more and more container terminals are deploying automated handling equipment to improve the overall productivity. As the equipment is often unmanned and automatically controlled, it is essential to have a formal scheduling method for generating exact work orders, preferably in a dynamic nature, to instruct the equipment to perform the corresponding tasks in realtime. Moreover, since operator intervention is not available online, efficient planning and scheduling are crucial to achieve satisfactory overall performance. In automated material handling, most existing literature deals with the scheduling of a single type of equipment, for instance the scheduling of automated guided vehicles (AGVs) and transfer cranes. However, due to the nature of material handling operations, the schedules of different types of equipment are highly interactive. In practice, the main loss of efficiency appears to be resulted from the schedules of automated equipment such as AGVs, stacker cranes (SCs), cargo hoists, conveyors, etc., which are not coordinated optimally. Most often, the individual or disjointed scheduling of the equipment may lead to low overall performance or even resulted in deadlocking situations. To address the very issue of optimal performance of a complete material handling task, this research deals with the integrated scheduling of more than one type of handling equipment with double cycle operations, in which the loading and the discharging operations can be performed alternatively. With this mode of operation, a multi objective optimization of the cooperating entities can be effectively performed in order to achieve an overall optimal performance of container handling in an automated port container terminal. An automated container terminal with three types of equipment, quay cranes (QCs), automated guided vehicles (AGVs) and automated yard cranes (AYCs) is considered in this study. Our objective is to construct a detailed schedule for all the QCs, AGVs and AYCs, such that the delay time of QCs, and the travel time of AGVs and AYCs are minimized. As the interaction between QCs, AGVs and AYCs has a great influence to the container handling process, the cooperating events are the basic scheduled objects. Therefore, the schedules we constructed determine the timing of the cooperating events between QCs and AGVs. Moreover, the cooperating events must be assigned to individual AGVs and the order and the timing of the events assigned to the same AGV must also be determined. Finally, for each of the AYC, as the corresponding tasks assigned are already known (since it is known a prior the specific stack lane a container is to be stored), our task is to determine the order and the timing of the cooperating events between the AGVs and the individual AYCs. A mixed-integer programming model is provided for the integrated scheduling problem with the objectives of minimizing the total delay time of QCs, and the total travel time of AGVs and AYCs. This problem is a NP-complete problem, for which the polynomial time is unlikely. To facilitate the solution procedure, a heuristic algorithm called multi-layer genetic algorithm (MLGA) is proposed. The main-layer genetic algorithm is to find the optimal sequence of the cooperating events between QCs and AGVs, while the sub-layer aims to find the sequence of the cooperating events of the individual AGVs, which actually deals with the AGV task assignment problems. As the sequence of the cooperating events between AGVs and individual AYCs is a subset of the optimal sequence of the cooperating events between QCs and AGVs obtained, this integrated scheduling problem is solved by the proposed MLGA. In the MLGA that we developed, the chromosomes are represented as order-