Container terminal visual berth distribution system and berth distribution method

Abstract

The invention relates to a container terminal visual berth distribution system and a berth distribution method, and belongs to the technical field of port management, and the system comprises a berth planning coordination module, a berth real-time allocation module, a berth adjustment optimization module, a visual operation module, a data analysis auxiliary module and a system performance monitoring module which are in signal connection with one another; wherein the berth planning coordination module outputs a berth planning scheme, the berth real-time allocation module outputs a berth allocation scheme, the berth adjustment optimization module outputs a berth adjustment scheme, and the visual operation module provides graphic display and operation of berths on a wharf, resource states and ship dynamics. Dynamic information and operation are fed back to the data analysis auxiliary module, and the data analysis auxiliary module provides data analysis results for the parking space planning coordination module, the parking space real-time allocation module and the parking space adjustment optimization module and assists in management decision making. According to the invention, rapid intelligent distribution and real-time distribution of berths can be carried out, and automation of wharf management is realized.

Description

Technical Field

[0001] The invention belongs to the technical field of port management, and in particular relates to a visualized berth allocation system and a berth allocation method for a container terminal. Background Art

[0002] Berth refers to the location in the port area where ships can dock. It is generally the length of the shoreline or the number of pontoons occupied by a standard ship type docking at the dock. A dock may consist of one or more berths depending on the layout and location. In order to ensure that ships can enter and exit the port safely and complete the loading and unloading of cargo, the dock needs to allocate berths. Since a dock berth can only serve one ship at the same time, but the ship is easily affected by wind, waves, and currents during navigation and cannot maintain a constant speed, resulting in the inability to arrive at the port on time, which in turn leads to the randomness of port operations. In addition, berth allocation needs to consider factors such as the size, draft, and cargo quality of the ship, so berth allocation is required.

[0003] At present, the traditional berth allocation method mainly relies on manual experience for ship scheduling planning, and generally lacks modern digital management methods, making it difficult to dynamically adjust and optimize the complex and changeable berth conditions. In addition, due to the limited number of terminal berths and the unreasonable berth design and operation methods, berths are often idle or overly congested. The number of automated ships involved in berth allocation is limited, which further increases the information asymmetry between staff and ship operators on the progress of berth allocation, resulting in low resource utilization and long response time. It is difficult to effectively track the real-time status and position of the ship, and it is impossible to achieve the best allocation effect. The links involving ship application, berth allocation, and operation plan adjustment are mainly manual and rely on the experience and judgment of the staff. In the event of emergencies (such as equipment failure, bad weather, etc.) or changes in demand, it is difficult to make quick adjustments, resulting in a further reduction in the efficiency of berth resource utilization. At present, most of the ship terminals are container terminals, which have higher requirements for the utilization efficiency of berths. Therefore, there is an urgent need for a container terminal berth allocation system that can optimize the utilization rate of berth resources, improve the efficiency and response speed of the entire berth allocation process, reduce the manpower and material consumption of staff during the berth allocation process, and ultimately achieve efficient management of terminal berth resources. Summary of the invention

[0004] The purpose of the present invention is to provide a container terminal visual berth allocation system and berth allocation method to address the problems existing in the prior art, so as to assist operators in clearly understanding the berth status and ship dynamics, facilitate timely adjustment of operation plans to comprehensively consider ship demand, berth availability and operation efficiency, improve the utilization efficiency and allocation rationality of terminal berth resources, reduce the cost of manual allocation, improve the ability to respond to emergencies, optimize resource allocation strategies, formulate scientific and reasonable berth planning, and improve overall operation efficiency.

[0005] The technical solution is as follows:

[0006] A visual berth allocation system for container terminals includes a berth planning and coordination module, a berth real-time allocation module, a berth adjustment and optimization module, a visual operation module, a data analysis auxiliary module and a system performance monitoring module, which are connected to each other through signals; wherein the berth planning and coordination module outputs a berth planning scheme to the berth real-time allocation module according to the arrival time of the ship and the loading and unloading demand; the berth real-time allocation module uses an algorithm to dynamically determine the berth of the ship based on the real-time berth and equipment status information provided by the visual operation module, and then outputs a berth allocation scheme to the berth adjustment and optimization module; the berth adjustment and optimization module adjusts the berth according to emergencies or changes. The berth allocation plan is optimized and reconfigured, and the berth adjustment plan is output to the berth planning coordination module and the berth real-time allocation module. After the visual operation module obtains the berth allocation plan, berth adjustment plan and ship status, it provides a graphical display and operation of berths, resource status and ship dynamics on the terminal, and feeds back the dynamic information and operations to the data analysis auxiliary module. The data analysis auxiliary module collects historical data and performs real-time analysis, obtains data from the berth planning coordination module and the berth real-time allocation module, and provides data analysis results to the berth planning coordination module, the berth real-time allocation module and the berth adjustment optimization module to assist management decision-making.

[0007] Furthermore, the system performance monitoring module and the data analysis auxiliary module include a central processing unit and a storage unit. The system performance monitoring module monitors the interaction between other modules to ensure the stability and efficiency of the system under high load. The data analysis auxiliary module integrates and synchronizes the data of each module to form log storage.

[0008] Furthermore, the berth real-time allocation module uses a particle swarm-genetic algorithm (PSO-GA) to dynamically optimize ship berth allocation based on real-time berth data, output berth allocation plans, and improve berth utilization efficiency. The particle swarm (PSO) algorithm has a fast convergence speed and focuses on efficiency, while the genetic (GA) algorithm prioritizes safety.

[0009] Furthermore, the visual operation module uses a graphical ship scheduling management interface to provide operators with an intuitive operation management view and a dock shoreline representation with a timeline. The graphical ship scheduling management interface consists of three parts: a list area for ships to be scheduled, a graphical ship scheduling area, and a crane resource utilization display area. The list area for ships to be scheduled displays detailed information on ships to be scheduled in list form. The crane resource utilization display area automatically maps and generates crane resource utilization status based on the ship scheduling plan data in the graphical ship scheduling area. The graphical ship scheduling area enables operators to perform dynamic ship scheduling operations by dragging ship graphic objects. The ship scheduling plan will scroll and refresh over time to keep the information real-time.

[0010] Furthermore, the ships in the waiting list area are divided into liner area, waiting area, pending area, temporary area and other areas through labels. Each item in the list contains the ship name, voyage number, time to meet the operating conditions, waiting time, captain, and fields can be added by users.

[0011] Furthermore, each ship graphic object is a rectangle, the length of the rectangle represents the length of the ship, the height of the rectangle represents the time occupied by the loading and unloading operations, and the color of the rectangle outline represents the different priority levels of the ship's waiting time; the upper and lower gray areas of the rectangle represent the berthing time and unberthing time occupied by the ship, respectively, and loading and unloading operations cannot be carried out during this period of time; the middle of the rectangle is the operation area, different colors are used to represent different operation states, and a rectangle with a triangular arrow represents the bow direction, and the color of the rectangle represents the nature of the ship; in the operation area, if the ship's current time has not arrived for berthing, it is in the pre-arranged but not berthed state, which is represented by orange; if the ship's current time is between the berthing time and the start time, it is in the berthing but not operating state, which is represented by blue; if the ship's current time is after the start time and the completion time is empty, it is in the operating state, which is represented by yellow; if the ship's current time is after the completion time and the actual unberthing time is empty, it is in the completed but not unberthed state, which is represented by light gray; the ship's actual unberthing time is the unberthed state, which is represented by purple.

[0012] A method for visualizing berth allocation at a container terminal comprises the following steps:

[0013] Step 1: The berth planning and coordination module adjusts the operation plan and resource allocation in real time based on the estimated arrival time of the ship and the loading and unloading requirements, and converts the configuration plan of berth and equipment resources into operation tasks;

[0014] Step 2: The berth real-time allocation module receives the job tasks and uses concurrent computing to optimize the berth configuration. The optimized berth plan will replace the original plan to improve resource utilization;

[0015] Step 3: When an emergency occurs, the berth adjustment optimization module quickly updates the particle speed and position through the optimization function according to the changes, reconfigures the berth, and generates a new berth adjustment plan; the optimization function is: Among them C carbon represents the carbon emission cost, C delay represents the cost of delayed departure of the ship, C anchorage represents the waiting cost at anchorage; the particle speed adjustment formula is: vi(t+1)=w·v i (t)+c1·r1·(p i -x i )+c2·r2·(gx i ), the particle position adjustment formula is: i (t+1)=x i (t)+v i (t+1), where v i (t) is the velocity of the ith particle, x i (t) is the position of the particle, p i and g are the individual optimal position and the global optimal position respectively, w is the inertia weight, c1 and c2 are acceleration constants, r1 and r2 are random numbers between [0, 1];

[0016] Step 4: The visual operation module provides operators with a graphical interface for real-time operation monitoring and berth allocation status. Operators perform ship arranging operations based on the dynamic display of berth allocation;

[0017] Step 5: The data analysis auxiliary module collects historical data and performs real-time analysis, including tidal data, ship displacement status, and ship displacement plan for the next 36 hours in the form of charts, and stores the analysis results as decision support information to assist operators in strategic planning;

[0018] Step 6: The system performance monitoring module continuously monitors the performance of the entire berth allocation system, optimizes the collaboration of each module, and ensures stable operation of the system under high load environment.

[0019] Furthermore, in step 2, the concurrent calculation uses a particle swarm algorithm and a genetic algorithm, and the specific steps are as follows:

[0020] Step 21: Initialize particles for each ship berth. If the total number of particles is N, each processing unit is responsible for initializing N / P particles, where P is the number of processing units: x i (0) = x min +(x max -x min )·rand(),i=1,2,…,N,v i (0) = v min +(v max -v min )·rand(),i=1,2,…,N;

[0021] Step 22: Calculate the fitness value of the particle: f i =f(x i ), i = 1, 2, ..., N;

[0022] Step 23: Each processing unit updates the individual optimal position p of the particle it is responsible for i Each processing unit aggregates its individual best position and finds the global best position g o :

[0023] Step 24: Each processing unit updates the velocity and position of the particle it is responsible for in parallel: v i (t+1)=ωv i (t)+c1r1(p i (t)-x i (t))+c2r2(g(t)-x i (t)), i=1, 2,..., N, x i (t+1)=x i (t)+v i (t+1), i=1, 2, ..., N, where ω is the inertia weight, c1 and c2 are acceleration constants, and r1 and r2 are random numbers between [0, 1];

[0024] Step 25: Perform genetic operations on particles to obtain the optimized berth configuration.

[0025] Furthermore, the genetic operation in step 25 includes the following steps:

[0026] Step 251: Each processing unit performs a selection operation in parallel, and selects a particle with a higher fitness among the particles it is responsible for as a parent:

[0027] Step 252: Each processing unit performs a crossover operation on the selected parent generation in parallel to generate new particles; new，i =αx parent1，i +(1-α)x parent2，i , α∈[0,1];

[0028] Step 253: Each processing unit performs mutation operations on some of the newly generated particles in parallel to increase the diversity of the population: x new，i =x new，i +mut·randn(), where mut is the coefficient of variation.

[0029] Furthermore, in step 4, the steps for the operator to perform the boat rowing operation are as follows:

[0030] Step 41: The system obtains data of the ships to be scheduled from the operation plan list, including ship name, voyage number, time to meet the operation conditions, and waiting time;

[0031] Step 42: Display the data in the liner area, the waiting area, and the waiting area of ​​the waiting ship list area;

[0032] Step 43: The operator drags the ship in the waiting ship list area to the graphical ship arrangement area, clicks on the ship to view or modify the ship's related information, selects the bow direction of left or right berthing, and enters the size corresponding to the berthing shoreline in the berth position. The system intuitively displays the ship arrangement plan in a graphical manner in the graphical ship arrangement area based on the shoreline, time and other information;

[0033] Step 44: The ship displacing plan is refreshed over time to ensure that the operator can grasp the latest ship displacing situation in real time.

[0034] Beneficial effects:

[0035] 1) The present invention adopts particle swarm genetic algorithm to reasonably integrate ship and berth information, plan the berth allocation and scheduling of ships, and can realize rapid and intelligent allocation of berths based on conditions such as ship size and expected arrival time, thereby realizing the automation and integration of terminal berth management.

[0036] 2) The present invention provides terminal operators with an intuitive and detailed operation monitoring interface, berth allocation view and a stable and real-time information feedback channel, so that they can perform real-time berth allocation and resource adjustment, reducing the possibility of operational errors and improving overall management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a structural schematic diagram of the visualized berth allocation system for container terminals of the present invention.

[0038] Figure 2 It is a logical schematic diagram of the method for visualizing berth allocation of container terminals according to the present invention.

[0039] Figure 3 This is a schematic diagram of the graphical boat management interface of the visual operation module. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. The directions or positional relationships indicated by the terms "upper", "lower", "front", "back", "left", "right", "bottom", "inside", "outside", etc. are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention:

[0041] like Figure 1 A container terminal visual berth allocation system is shown, comprising a berth planning coordination module, a berth real-time allocation module, a berth adjustment optimization module, a visual operation module, a data analysis auxiliary module and a system performance monitoring module which are connected to each other through signals; wherein the berth planning coordination module outputs a berth planning scheme to the berth real-time allocation module according to the arrival time of the ship and the loading and unloading demand; the berth real-time allocation module uses an algorithm to dynamically determine the berth of the ship based on the real-time berth and equipment status information provided by the visual operation module, and then outputs a berth allocation scheme to the berth adjustment optimization module; the berth adjustment optimization module outputs a berth allocation scheme to the berth adjustment optimization module based on emergencies or changes. The berth allocation plan is optimized and reconfigured, and the berth adjustment plan is output to the berth planning and coordination module and the berth real-time allocation module. After the visual operation module obtains the berth allocation plan, berth adjustment plan and ship status, it provides a graphical display and operation of berths, resource status and ship dynamics on the terminal, and feeds back the dynamic information and operations to the data analysis auxiliary module. The data analysis auxiliary module collects historical data and performs real-time analysis, obtains data from the berth planning and coordination module and the berth real-time allocation module, and provides data analysis results to the berth planning and coordination module, the berth real-time allocation module and the berth adjustment optimization module to assist management decisions.

[0042] The system performance monitoring module and the data analysis auxiliary module include a central processing unit and a storage unit. The system performance monitoring module monitors the interaction between other modules to ensure the stability and efficiency of the system under high load. The data analysis auxiliary module integrates and synchronizes the data of each module to form log storage.

[0043] The berth real-time allocation module uses particle swarm-genetic algorithm to dynamically optimize ship berth allocation based on real-time berth data, output berth allocation plan, and improve berth utilization efficiency. The particle swarm algorithm has a fast convergence speed and focuses on efficiency, while the genetic algorithm prioritizes safety.

[0044] The visual operation module uses a graphical ship management interface to provide operators with an intuitive operation management view and a timeline representation of the dock shoreline, such as Figure 3The graphical ship scheduling management interface shown is composed of three parts: the list area of ​​ships to be scheduled, the graphical ship scheduling area, and the bridge crane resource utilization display area. The list area of ​​ships to be scheduled displays detailed information of ships to be scheduled in the form of a list. The bridge crane resource utilization display area automatically maps and generates the utilization of bridge crane resources according to the ship scheduling plan data in the graphical ship scheduling area. The graphical ship scheduling area enables operators to perform dynamic ship scheduling operations by dragging ship graphic objects. The ship scheduling plan will scroll and refresh over time to keep the real-time information; the ships in the list area of ​​ships to be scheduled are divided into liner area, waiting area, pending area, temporary area, and other areas through labels. Each item in the list contains the ship name, voyage, time to meet the operating conditions, waiting time, captain, and fields can be added by users; each ship graphic object is a rectangle, the length of the rectangle represents the length of the ship, and the height of the rectangle represents loading and unloading The time occupied by the operation, the color of the rectangle outline indicates the different priority levels of the ship's waiting time; the upper and lower gray areas of the rectangle respectively indicate the berthing time and unberthing time occupied by the ship, during which loading and unloading operations cannot be carried out; the middle of the rectangle is the operation area, different colors are used to indicate different operation status, and a rectangle with a triangular arrow indicates the bow direction, and the color of the rectangle indicates the nature of the ship; in the operation area, if the ship's current time has not arrived for berthing, it is in the pre-arranged but not berthed state, which is indicated by orange; the ship's current time is between the berthing time and the start time, which is in the berthing but not operating state, which is indicated by blue; when the ship's current time is after the start time and the completion time is empty, it is in the operating state, which is indicated by yellow; when the ship's current time is after the completion time and the actual unberthing time is empty, it is in the completed but not unberthed state, which is indicated by light gray; the ship's actual unberthing time is the unberthed state, which is indicated by purple.

[0045] like Figure 2 A method for visualizing berth allocation at a container terminal is shown, comprising the following steps:

[0046] Step 1: The berth planning and coordination module adjusts the operation plan and resource allocation in real time based on the estimated arrival time of the ship and the loading and unloading requirements, and converts the configuration plan of berth and equipment resources into operation tasks;

[0047] Step 2: The berth real-time allocation module receives the job tasks and uses concurrent computing to optimize the berth configuration. The optimized berth plan will replace the original plan to improve resource utilization;

[0048] Step 3: When an emergency occurs, the berth adjustment optimization module quickly updates the particle speed and position through the optimization function according to the changes, reconfigures the berth, and generates a new berth adjustment plan; the optimization function is: Among them C carbon represents the carbon emission cost, C delay represents the cost of delayed departure of the ship, C anchorage represents the cost of waiting at anchorage; the particle speed adjustment formula is: vi (t+1)=w·v i (t)+c1·r1·(p i -x i )+c2·r2·(gx i ), the particle position adjustment formula is: i (t+1)=x i (t)+v i (t+1), where v i (t) is the velocity of the ith particle, x i (t) is the position of the particle, p i and g are the individual optimal position and the global optimal position respectively, w is the inertia weight, c1 and c2 are acceleration constants, r1 and r2 are random numbers between [0, 1];

[0049] Step 4: The visual operation module provides operators with a graphical interface for real-time operation monitoring and berth allocation status. Operators perform ship arranging operations based on the dynamic display of berth allocation;

[0050] Step 5: The data analysis auxiliary module collects historical data and performs real-time analysis, including tidal data, ship displacement status, and ship displacement plan for the next 36 hours in the form of charts, and stores the analysis results as decision support information to assist operators in strategic planning;

[0051] Step 6: The system performance monitoring module continuously monitors the performance of the entire berth allocation system, optimizes the collaboration of each module, and ensures stable operation of the system under high load environment.

[0052] In step 2, the concurrent calculation uses a particle swarm algorithm and a genetic algorithm. The specific steps are as follows:

[0053] Step 21: Initialize particles for each ship berth. If the total number of particles is NN, each processing unit is responsible for initializing N / P particles, where P is the number of processing units: x i (0) = x min +(x max -x min )·rand(),i=1,2,…,N,v i (0) = v min +(v max -v min )·rand(),i=1,2,…,N;

[0054] Step 22: Calculate the fitness value of the particle: f i =f(x i ), i=1, 2, ..., N;

[0055] Step 23: Each processing unit updates the individual optimal position p of the particle it is responsible for i Each processing unit aggregates its individual best position and finds the global best position g o :

[0056] Step 24: Each processing unit updates the velocity and position of the particle it is responsible for in parallel: v i (t+1)=ωv i (t)+c1r1(p i (t)-x i (t))+c2r2(g(t)-x i (t)), i=1, 2,..., N, x i (t+1)=x i (t)+v i (t+1), i=1, 2, ..., N, where ω is the inertia weight, c1 and c2 are acceleration constants, and r1 and r2 are random numbers between [0, 1];

[0057] Step 25: Perform genetic operations on particles to obtain the optimized berth configuration.

[0058] The genetic operation in step 25 includes the following steps:

[0059] Step 251: Each processing unit performs a selection operation in parallel, and selects a particle with a higher fitness among the particles it is responsible for as a parent:

[0060] Step 252: Each processing unit performs a crossover operation on the selected parent generation in parallel to generate new particles; new，i =αx parent1，i +(1-α)x parent2，i , α∈[0,1];

[0061] Step 253: Each processing unit performs mutation operations on some of the newly generated particles in parallel to increase the diversity of the population: x new，i =x new，i +mut·randn(), where mut is the coefficient of variation.

[0062] In step 4, the operator performs the following steps to perform the boat rowing operation:

[0063] Step 41: The system obtains data of the ships to be scheduled from the operation plan list, including ship name, voyage number, time to meet the operation conditions, and waiting time;

[0064] Step 42: Display the data in the liner area, the waiting area, and the waiting area of ​​the waiting ship list area;

[0065] Step 43: The operator drags the ship in the waiting ship list area to the graphical ship arrangement area, clicks on the ship to view or modify the ship's related information, selects the bow direction of left or right berthing, and enters the size corresponding to the berthing shoreline in the berth position. The system intuitively displays the ship arrangement plan in a graphical manner in the graphical ship arrangement area based on the shoreline, time and other information;

[0066] Step 44: The ship displacing plan is refreshed over time to ensure that the operator can grasp the latest ship displacing situation in real time.

[0067] Example 1: When visualizing berth planning for container ships arriving at the port, the berth planning coordination module adjusts the operation plan and resource allocation in real time based on the estimated arrival time of the ship and the loading and unloading requirements, and converts the configuration plan of berths and equipment resources into operation tasks; the berth real-time allocation module receives the operation tasks, and uses the particle swarm algorithm and genetic algorithm to concurrently calculate and optimize the berth configuration. The optimized berth plan will replace the original plan. If an emergency occurs and the container ship cannot arrive at the port in time, the berth adjustment optimization module will quickly reconfigure the berth according to the changes and generate a new adjustment plan through the optimization function; at the same time, the operator can perform ship scheduling operations through the graphical interface of the visualization operation module. The specific operations are as follows: the system obtains the data of the ship to be scheduled from the operation plan list, including the ship name, voyage number, time to meet the operation conditions, and waiting time, and displays the data in the liner area of ​​the list of ships to be scheduled , waiting area, and pending area. The operator drags the ship in the waiting ship list area to the graphical ship arrangement area, clicks on the ship to view or modify the relevant information of the ship, selects the bow direction of left or right, and enters the size corresponding to the berthing shoreline in the berth position. The system displays the ship arrangement plan in a graphical way in the graphical ship arrangement area based on the shoreline, time and other information. At this time, the ship arrangement plan is refreshed over time to ensure that the operator can grasp the latest ship arrangement situation in real time; the data analysis auxiliary module collects historical data and performs real-time analysis, including tidal data, ship arrangement status and ship arrangement plan in the next 36 hours in the form of charts, and stores the analysis results as decision support information to assist operators in strategic planning; the system performance monitoring module continuously monitors the performance of the entire berth allocation system, optimizes the collaboration of various modules, and ensures stable operation of the system under high load conditions.

[0068] Assume that there are 5 ships that need to be allocated berths at the terminal. The arrival time, departure time, berth requirements and priority of the ships are as follows:

[0069] Vessel Number Arrival time Departure Time Berth demand Priority 1 2:00 16:00 2 high 2 13:00 18:00 1 middle 3 13:00 24:00 3 Low 4 14:00 21:00 1 high 5 19:00 23:00 2 Low

[0070] Goal: Minimize total waiting time and ensure high priority vessels get berth first.

[0071] Particle swarm algorithm parameters: number of particles = 50, inertia weight ω = 0.5, acceleration constants c1 = 1.5, c2 = 1.5;

[0072] Genetic algorithm parameters: crossover probability = 0.8, mutation probability = 0.1;

[0073] Minimize total waiting time: Priority weighting:

[0074] Fitness function calculation, particle velocity and position update, and genetic operations are all executed in the parallel computing module.

[0075] After several iterations, the optimized berth allocation scheme is as follows:

[0076]

[0077]

[0078] Finally, the optimized berth allocation plan is output and visualized.

[0079] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the principles and spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A container terminal visual berth allocation system, characterized by: It includes a berth planning and coordination module, a berth real-time allocation module, a berth adjustment and optimization module, a visual operation module, a data analysis auxiliary module and a system performance monitoring module, which are connected to each other through signals; the berth planning and coordination module outputs the berth planning scheme to the berth real-time allocation module according to the ship's arrival time and loading and unloading requirements; the berth real-time allocation module uses an algorithm to dynamically determine the ship's berth based on the real-time berth and equipment status information provided by the visual operation module, and then outputs the berth allocation scheme to the berth adjustment and optimization module; the berth adjustment and optimization module adjusts the berth allocation scheme according to emergencies or changes. Optimize and reconfigure, output berth adjustment plans to the berth planning and coordination module and the berth real-time allocation module. After the visual operation module obtains the berth allocation plan, berth adjustment plan and ship status, it provides a graphical display and operation of berths, resource status and ship dynamics on the dock, and feeds back dynamic information and operations to the data analysis auxiliary module. The data analysis auxiliary module collects historical data and performs real-time analysis, obtains data from the berth planning and coordination module and the berth real-time allocation module, and provides data analysis results to the berth planning and coordination module, the berth real-time allocation module and the berth adjustment optimization module to assist management decisions.

2. The container terminal visual berth allocation system according to claim 1, characterized in that: The system performance monitoring module and data analysis auxiliary module include a central processing unit and a storage unit. The system performance monitoring module monitors the interaction of other modules to ensure the stability and efficiency of the system under high load. The data analysis auxiliary module integrates and synchronizes the data of each module to form log storage.

3. The container terminal visual berth allocation system according to claim 1, characterized in that: The berth real-time allocation module adopts a particle swarm-genetic algorithm to dynamically optimize the ship berth allocation according to the real-time data of the berth, outputs a berth allocation plan, and improves the berth utilization efficiency. The particle swarm algorithm has a fast convergence speed and focuses on efficiency, while the genetic algorithm prioritizes safety.

4. The container terminal visual berth allocation system according to claim 1, characterized in that: The visualization operation module uses a graphical ship scheduling management interface to provide operators with an intuitive operation management view and a dock shoreline representation with a timeline. The graphical ship scheduling management interface consists of three parts: a list area for ships to be scheduled, a graphical ship scheduling area, and a bridge crane resource utilization display area. The list area for ships to be scheduled displays detailed information on ships to be scheduled in list form. The bridge crane resource utilization display area automatically maps and generates bridge crane resource utilization based on the ship scheduling plan data in the graphical ship scheduling area. The graphical ship scheduling area enables operators to perform dynamic ship scheduling operations by dragging ship graphic objects. The ship scheduling plan will scroll and refresh over time to keep the real-time information.

5. The container terminal visual berth allocation system according to claim 4, characterized in that: The ships in the waiting list area are divided into liner area, waiting area, pending area, temporary area and other areas by labels. Each item in the list includes the ship name, voyage, time to meet the operating conditions, waiting time, captain, and fields can be added by users.

6. The container terminal visual berth allocation system according to claim 4, characterized in that: Each of the ship graphic objects is a rectangle, the length of the rectangle represents the length of the ship, the height of the rectangle represents the time occupied by the loading and unloading operations, and the color of the rectangle outline represents the different priority levels of the ship's waiting time; the upper and lower gray areas of the rectangle represent the berthing time and the unberthing time occupied by the ship, respectively, and loading and unloading operations cannot be carried out during this period of time; the middle of the rectangle is the operation area, and different colors are used to represent different operation states, and a rectangle with a triangular arrow represents the bow direction, and the color of the rectangle represents the nature of the ship; in the operation area, if the ship's current time has not arrived for berthing, it is in the pre-arranged non-berthing state, which is represented by orange; the current time of the ship is between the berthing time and the start time, it is in the berthing non-operating state, which is represented by blue; when the current time of the ship is after the start time and the completion time is empty, it is in the operating state, which is represented by yellow; when the current time of the ship is after the completion time and the actual unberthing time is empty, it is in the completed but not unberthed state, which is represented by light gray; the actual unberthing time of the ship is the unberthed state, which is represented by purple.

7. A method for visualizing berth allocation at a container terminal, characterized in that: The following steps are involved: Step 1: The berth planning and coordination module adjusts the operation plan and resource allocation in real time based on the estimated arrival time of the ship and the loading and unloading requirements, and converts the configuration plan of berth and equipment resources into operation tasks; Step 2: The berth real-time allocation module receives the job tasks and uses concurrent computing to optimize the berth configuration. The optimized berth plan will replace the original plan to improve resource utilization; Step 3: When an emergency occurs, the berth adjustment optimization module quickly updates the particle speed and position through the optimization function according to the changes, reconfigures the berth, and generates a new berth adjustment plan; the optimization function is: Among them C carbon represents the carbon emission cost, C delay represents the cost of delayed departure of the ship, C anchorage It indicates the cost of waiting at anchorage; The particle velocity adjustment formula is: i (t+1)=w·v i (t)+c1·r1·(p i -x i )+c2·r2·(gx i ), the particle position adjustment formula is: i (t+1)=x i (t)+v i (t+1), where v i (t) is the velocity of the ith particle, x i (t) is the position of the particle, p i and g are the individual optimal position and the global optimal position respectively, w is the inertia weight, c1 and c2 are acceleration constants, r1 and r2 are random numbers between [0, 1]; Step 4: The visual operation module provides operators with a graphical interface for real-time operation monitoring and berth allocation status. Operators perform ship arranging operations based on the dynamic display of berth allocation; Step 5: The data analysis auxiliary module collects historical data and performs real-time analysis, including tidal data, ship displacement status, and ship displacement plan for the next 36 hours in the form of charts, and stores the analysis results as decision support information to assist operators in strategic planning; Step 6: The system performance monitoring module continuously monitors the performance of the entire berth allocation system, optimizes the collaboration of each module, and ensures stable operation of the system under high load environment.

8. The container terminal visualized berth allocation system and berth allocation method according to claim 7, characterized in that: In step 2, the concurrent calculation uses a particle swarm algorithm and a genetic algorithm, and the specific steps are as follows: Step 21: Initialize particles for each ship berth. If the total number of particles is N, each processing unit is responsible for initializing N / P particles, where P is the number of processing units: x i (0)=x min +(x max -x min )·rand(),i=1,2,…,N, v i (0)=v min +(v max -v min )·rand(),i=1,2,...,N; Step 22: Calculate the fitness value of the particle: f i =f(x i ), i=1, 2, ..., N; Step 23: Each processing unit updates the individual optimal position p of the particle it is responsible for i , each processing unit aggregates its individual best position and finds the global best position g o : Step 24: Each processing unit updates the velocity and position of the particle it is responsible for in parallel: v i (t+1)=ωv i (t)+c1r1(p i (t)-x i (t))+c2r2(g(t)-x i (t)), i=1, 2,..., N, x i (t+1)=x i (t)+v i (t+1), i=1, 2, ..., N, where ω is the inertia weight, c1 and c2 are acceleration constants, and r1 and r2 are random numbers between [0, 1]; Step 25: Perform genetic operations on particles to obtain the optimized berth configuration.

9. The container terminal visualized berth allocation system and berth allocation method according to claim 8, characterized in that: The genetic operation in step 25 comprises the following steps: Step 251: Each processing unit performs a selection operation in parallel, and selects a particle with a higher fitness among the particles it is responsible for as a parent: Step 252: Each processing unit performs a crossover operation on the selected parent generation in parallel to generate new particles; new，i =αx parent1，i +(1-α)x parent2，i , α∈[0,1]; Step 253: Each processing unit performs mutation operations on some of the newly generated particles in parallel to increase the diversity of the population: x new，i =x new，i +mut·randn(), where mut is the coefficient of variation.

10. The container terminal visualized berth allocation system and berth allocation method according to claim 7, characterized in that: In step 4, the operator performs the following steps to perform the boat rowing operation: Step 41: The system obtains data of the ships to be scheduled from the operation plan list, including ship name, voyage number, time to meet the operation conditions, and waiting time; Step 42: Display the data in the liner area, the waiting area, and the waiting area of ​​the waiting ship list area; Step 43: The operator drags the ship in the waiting ship list area to the graphical ship arrangement area, clicks on the ship to view or modify the ship's related information, selects the bow direction of left or right berthing, and enters the size corresponding to the berthing shoreline in the berth position. The system intuitively displays the ship arrangement plan in a graphical manner in the graphical ship arrangement area based on the shoreline, time and other information; Step 44: The ship displacing plan is refreshed over time to ensure that the operator can grasp the latest ship displacing situation in real time.

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