Modeling And Optimization Of Berth Scheduling In Container Terminal Based On Multi-agent System

With the acceleration of economic globalization, economic and trade exchanges between countries in the world are becoming more and more frequent. Container transport by sea has become an essential part of the global supply chain. As a meeting point of maritime and land transportation, container terminal plays an important role in the international transport network. The operational process of logistics in container terminal shows dynamics, random and complexity increasingly and proposes many new problems which must be solved as soon as possible. Especially, how to model and optimize the sub-system of berth scheduling and coordinate the sub-system mentioned above with the other sub-systems in the container terminal are urgent problems waiting to be solved. In order to enhance the operational efficiency and service level, the operation scheduling problems in container terminals have attracted more and more attention and become a hotspot in the field of logistics optimization. This dissertation chiefly addresses the modeling and optimization of berth scheduling in container terminals based on Multi-agent system. The main contents are as follows:This dissertation firstly studies and proposes the MAS based architecture model of the operational scheduling system of logistics in container terminals in Chapter 2. Chapter 2 firstly analyzes the basic constituents, structures and process flows of the logistics operational system of container terminals by the numbers and designs the MAS based architecture model of the system. The system model is composed of the five class agents such as mission planning agents, dynamic cell agents, container vessel agents, resource management agents and resource agents. Chapter 2 then defines the basic functions, basic structures, communication mode and interaction mode. The dissertation realizes the relationship of dynamic subordination and structure of dynamic control by introducing of the dynamic cell. Chapter 2 lastly designs the mechanism of interaction and collaboration among the agents.This dissertation then studies and proposes the robust berth allocation model based on ant colony optimization in Chapter 3. Based on the MAS architecture model of logistics operation in container terminals, the dissertation regards total planning delay time of vessels in the terminals as service measure, introduces buffer time as robust measure and proposes the model of robust and discrete berth allocation. In the model the physical conditions and handling capability of the berths is taken into account and the trade-off between the service and robustness of berth allocation planning. The dissertation applies ant colony optimization to solve the model. The simulation tests reveal that the robust berth allocation plan through the method in this dissertation has the significantly better ability of anti-disturbance than that by the traditional method under the uncertain environment.This dissertation finally studies and proposes a dynamic and real-time scheduling model of quay crane based on CNP in Chapter 4. However enough the robustness of the berth allocation plan is, it is inevitable that some container vessels delay in the container terminal. Therefore, in order to make logistics operations implemented successfully and further increase the anti-disturbance ability of container terminals, the dissertation proposes a dynamic and real-time scheduling model of quay crane under the environment of the MAS architecture model in the mission implementing phase. The model takes the horizontal shift of quay cranes into consideration and makes full use of idle quay cranes, smoothing the impact on operation planning of container terminals by random disturbance. The model applies the CNP mechanism to realize the dynamic and real-time scheduling for the quay cranes. The simulation tests indicate that this scheduling method for the quay cranes in the implementing phase may further increase robustness of the logistics operational system of container terminals.