Tide and weather linkage scheduling method oriented to port operation collaboration

Abstract

The invention relates to the technical field of collaborative scheduling management, in particular to a tide and weather linkage scheduling method for port operation collaboration, which comprises the following steps of: setting a benchmark, creating a virtual time axis, the initial state of the virtual time axis being a standard uniform elapsed time axis; marking an effective operation time window on the virtual time axis according to forecast tide data; performing correction according to the forecast meteorological data to generate a deformation time axis; calculating a starting time point and duration of each operation link on a deformation time axis, and reversely deducing a collaborative operation instruction sequence to form a final scheduling scheme; and dynamically adjusting the deformation time axis, and triggering rolling optimization of the final scheduling scheme. According to the method, it is guaranteed that the scheduling scheme is always unfolded around the core target of safe departure, time consumption of non-critical paths is reduced to the maximum extent, and the scheduling failure problem that in a traditional method, scheduling is completed, but departure fails is avoided.

Description

Technical Field

[0001] This invention relates to the field of collaborative scheduling and management technology, and in particular to a tidal and meteorological linkage scheduling method for port operation collaboration. Background Technology

[0002] Port scheduling is a multi-stage collaborative process integrating vessel berthing and departure, loading and unloading operations, truck transportation, and yard operations. The rationality of its scheduling plan directly affects vessel turnaround efficiency and port resource utilization. Current mainstream port scheduling methods are mostly based on static time windows, predefined operation paths, and resource allocation rules. While these methods can cover routine operational processes, they generally suffer from slow response, high plan failure rates, and delayed resource allocation when facing complex and frequently changing external environmental conditions, making it difficult to meet the needs of refined and highly reliable collaborative scheduling.

[0003] Taking tidal conditions as an example, for vessels with large drafts, berthing and unberthing operations are highly dependent on tidal changes. Existing scheduling systems only refer to predicted tidal highs or set fixed operation windows, lacking dynamic perception and fine-grained scheduling control of the entire tidal change process. This easily leads to operation interruptions or delays due to actual tidal heights being lower than expected. Meanwhile, meteorological conditions such as wind speed, precipitation, and visibility have a significant impact on quay crane lifting operations, container truck operations, and yard operations. However, traditional methods typically use "whether operation is feasible" as a coarse-grained judgment criterion, failing to explicitly model the impact of meteorological changes on operational efficiency, and even more so, failing to incorporate it into the scheduling plan generation process.

[0004] Furthermore, most existing technologies employ a forward-looking scheduling logic that starts from the operational start point. This means that the operational sequence of quay cranes, container trucks, and storage yards is calculated sequentially from the moment a ship berths. When faced with strong constraints such as tidal closures or deteriorating weather, these technologies often lack the ability to "backtrack to find the optimal operational path from the endpoint," leading to a risk of logical breakage in the overall scheduling chain. Especially in complex scenarios with concentrated ship berthing and frequent weather changes, forward-looking scheduling is highly likely to result in locally optimal but overall infeasible outcomes. Summary of the Invention

[0005] This invention provides a tidal and meteorological linkage scheduling method for port operation collaboration. This port operation collaborative scheduling method can integrate the dynamic characteristics of tidal and meteorological data, and has environmental adaptability and reconfigurable scheduling capabilities, fundamentally improving the overall controllability of the operation chain.

[0006] A tidal and meteorological coordinated scheduling method for port operations includes the following steps: S1. Construct a dynamic virtual timeline: Using the first work plan generated for the ships to be scheduled as a benchmark, create a virtual timeline corresponding to future work periods. The initial state of this virtual timeline is a standard uniform elapsed timeline. S2. Time Axis Deformation Correction: Obtain forecast tidal data and forecast meteorological data for future operation periods; mark effective operation time windows on the virtual time axis based on the forecast tidal data; correct the time flow velocity within the effective operation time windows based on the forecast meteorological data to generate a deformed time axis, wherein the time flow velocity is positively correlated with the work environment friendliness. S3. Generate a collaborative scheduling scheme based on the deformed time axis: On the deformed time axis, recalculate the start time and duration of each operation link, and deduce the collaborative operation instruction sequence of ships, quay cranes, container trucks and yard equipment in reverse to form the final scheduling scheme; S4. Dynamic maintenance of the time axis: During the operation, the deformed time axis is dynamically adjusted according to the deviation between real-time tidal and meteorological data and forecast values, and the rolling optimization of the final scheduling scheme is triggered.

[0007] Optionally, S1 includes determining the start time point and the end time point of the virtual time axis, wherein the start time point is the planned start time of the earliest work step in the first work plan, and the end time point is the planned end time of the latest work step.

[0008] Optionally, S1 further includes initializing the virtual timeline so that it flows uniformly at the rate of standard physical time between the start time point and the end time point, and marking the initial time nodes corresponding to the key operation links in the first operation plan.

[0009] Optionally, obtaining the forecast tidal data and forecast meteorological data for the future operation period specifically includes obtaining the time-matched tidal forecast curve and meteorological forecast curve within the future operation period from the port data source interface, extracting the continuous time period from the tidal forecast curve where the tide height meets the safe operation conditions based on the port channel water depth and the ship's draft, and mapping the continuous time period to the virtual time axis and marking it as the effective operation time window.

[0010] Optionally, S2 includes converting the element values ​​in the weather forecast curve into corresponding time flow velocity coefficients in real time based on a preset weather-efficiency mapping function. The lower the wind speed, the less precipitation, and the higher the visibility, the closer the time flow velocity coefficient is to 1, indicating that time passes faster and the operation efficiency is higher. Conversely, the time flow velocity coefficient approaches 0, indicating that time passes slower and the operation efficiency is lower.

[0011] Optionally, S2 further includes multiplying each physical time unit within the effective operation time window by the corresponding time flow velocity coefficient, thereby stretching or compressing the uniformly flowing physical time axis. Specifically, within the effective operation time window, based on the time flow velocity coefficient at each time point, a weighted integral is performed on the physical time to generate a deformed time axis. The time position of the deformed time axis at any physical time point t is determined by the time flow velocity integral from the virtual time axis starting point to that time point t, and the cumulative correction is only performed on the time period within the effective operation time window to construct a non-uniform deformed time axis that reflects changes in operation efficiency.

[0012] Optionally, S3 includes performing a reverse spatiotemporal extrapolation, taking the end point of the last valid operating time window marked on the deformation time axis as the final anchorage time at which the ship must depart, and performing reverse extrapolation calculations on the deformation time axis starting from the final anchorage time.

[0013] Optionally, the reverse deduction calculation specifically includes: a. Calculate the time point for stopping loading and unloading operations based on the standard time consumption for ship departure operations; b. Based on the actual time flow velocity corresponding to the time point when the loading and unloading operation stops on the deformation time axis and the total amount of goods to be loaded and unloaded, calculate the total time required for the quay crane operation, and thus determine the start time point of the quay crane operation. c. Based on the quay crane operation sequence, yard location, and traffic efficiency on the deformation time axis, assign transportation batches and routes to each truck, and calculate its round-trip time sequence between the yard and the quay crane; d. Based on the arrival time sequence of the container trucks, generate corresponding yard container retrieval or storage operation instruction sequences for the yard crane equipment; e. Sort and integrate all the equipment operation instructions obtained from the reverse calculation according to their corresponding physical time points to form the final scheduling scheme.

[0014] Optionally, in S4: during operation, real-time tidal and meteorological data streams are continuously accessed, and the deviation values ​​between them and the corresponding forecast tidal and meteorological data used in S2 are calculated. Trigger thresholds are set for tidal height deviation and deviations of various meteorological elements respectively. When the absolute value of any deviation value continuously exceeds its corresponding trigger threshold and reaches a preset duration, the deformation time axis is dynamically adjusted, and the rolling optimization process is immediately triggered. Based on the updated or new deformation time axis, the reverse deduction in S3 is automatically re-executed to generate a new collaborative operation instruction sequence, and the updated instructions are immediately sent to the affected operation equipment.

[0015] Optionally, the dynamic adjustment of the deformation time axis specifically includes: a. Local deformation: If the deviation occurs during the current or upcoming work period, the time flow rate of the corresponding local segment of the deformation time axis is corrected in real time based on real-time data to generate an updated deformation time axis; b. Global Reconstruction: If the deviation indicates a significant change in future environmental trends, the original timeline is discarded, and S2 is re-executed using the latest forecast data as input to construct a completely new deformed timeline.

[0016] The beneficial effects of this invention are: This invention introduces the concept of a virtual time axis, mapping the traditional physical passage of time to a dynamic time system influenced by the operational environment. Through tidal window extraction and a meteorological-efficiency mapping function, it achieves local stretching and compression of the time axis, thereby expressing the operational feasibility at each moment. Compared to existing methods that rely on static time periods for scheduling, this solution no longer treats time as a uniform background variable but actively models it as a function of the operational environment. This enhances the fault tolerance and predictive scheduling capabilities against disturbances such as severe weather and tidal changes. This "deformed time axis" constitutes the underlying supporting logic for the entire system's scheduling modeling, representing a structural innovation distinct from existing technologies.

[0017] This invention differs from traditional forward scheduling strategies that start scheduling from berthing and work backward. Instead, it employs a reverse-engineering mechanism with the end of the effective tidal operation window as a rigid anchor point. The scheduling system starts from the latest time the vessel must depart and works backward to determine the start time and duration of each task on a variable timeline, achieving an integrated closed-loop time sequence from unloading to quay cranes to container trucks to the yard. Especially under conditions of limited operating time and frequent environmental fluctuations, this mechanism ensures that the scheduling plan always revolves around the core objective of safe departure, minimizing time consumption on non-critical paths and avoiding the scheduling failure problem common in traditional methods where plans are completed but departure fails.

[0018] This invention introduces a closed-loop mechanism of "deviation monitoring – triggering – local correction / global reconstruction – rolling scheduling" in the scheduling execution phase. By monitoring the continuous deviation between real-time tidal and meteorological data and forecast values, and combining adjustable deviation thresholds and duration settings, it realizes conditional triggering and granular controllable updates for rolling optimization. When the deviation is local, deformation correction is performed only on the local time period. When there is a trend deviation, the time axis is globally reconstructed and a new scheduling plan is automatically derived, ensuring that the entire scheduling system has the stability control capability to adapt to changes in the actual situation. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the dynamic maintenance of the time axis according to an embodiment of the present invention. Detailed Implementation

[0021] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. For some well-known technologies, those skilled in the art may also use other alternative methods to implement the invention. Moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0022] like Figures 1-2 As shown, the tidal and meteorological linkage scheduling method for port operation coordination includes the following steps: S1. Construct a dynamic virtual timeline: Using the first operation plan generated for the ships to be scheduled as a benchmark, create a virtual timeline corresponding to future operation periods. The initial state of this virtual timeline is a standard uniform elapsed timeline.

[0023] The first operational plan refers to the preliminary operational arrangement generated in advance for vessels to be scheduled before scheduling optimization. This arrangement is based on conventional scheduling logic and does not yet consider the dynamic impact of environmental factors such as tides and weather. The first operational plan is usually automatically generated by the port scheduling system based on vessel forecasts, operational requests, and terminal resource conditions. It clearly lists the sequence of multiple operational stages from vessel berthing and loading / unloading operations to departure; it covers various operational objects, including vessels (berthing, departure, loading / unloading), quay cranes (container lifting start and end times), container trucks (container transshipment), and yard equipment (stacking and retrieving operations); each operational stage includes a planned start time and a planned end time; the first operational plan includes operational objects, operational content, and planned time periods; for each type of operational content, the first operational plan lists its planned start and end times as operational tasks.

[0024] The virtual timeline does not cover all days or any arbitrary time range, but rather precisely revolves around all the scheduled tasks in the first task plan, with its boundaries (start and end points) determined by the time periods of these tasks.

[0025] S1 is as follows: S11, set the boundaries of the virtual timeline to the earliest start time and latest end time of the work steps involved in the first work plan, and determine the start and end time points, i.e.: ; ; in, This represents the set of all work steps in the first work plan. Indicates the first The planned start time for each work step. Indicates the first The planned end time for each work step. Indicates the start time of the virtual timeline. Indicates the end time of the virtual timeline.

[0026] The earliest start time refers to the planned start time of the earliest operation among all operational steps in the first work plan. For example, this could be the planned berthing time of a ship. The latest finish time refers to the planned finish time of the last operation completed among all operational steps in the first work plan, such as the time when the last truckload of containers is transported. The goal of constructing the virtual timeline is to perform fine-grained scheduling control and optimization within this time interval. By using this as a boundary, computational resources are saved, focusing only on the critical time periods of the current batch of operations and avoiding redundant calculations.

[0027] S12, Initialize the virtual timeline: In the interval Build a virtual timeline Its rate of time elapses is consistent with standard physical time. Let: ;in: Represents the relationship between the virtual timeline and physical time. The corresponding virtual time, This indicates that the virtual timeline is synchronized with physical time at the same speed in the initial state, that is, it flows uniformly.

[0028] S13, Marking Key Time Nodes: Let the set of key task steps in the first task plan be... Then in the virtual timeline Mark the set of key nodes: ;in, This refers to a set of critical operational steps, including berthing, loading / unloading, and transshipment. Indicates the first Planned start times for each key operational step. This represents a set of key time points used to guide subsequent scheduling calculations. Indicates to the first The planned start time of each key operational step in terms of physical time. This is mapped to the corresponding time position on the virtual timeline.

[0029] Key operational steps From the complete set of work plans This refers to a subset of operational processes that are of scheduling importance. For example, in port operations, these critical processes include ship berthing, commencement of loading, truck arrival, and completion of critical path containers.

[0030] Indicates each critical operational step The planned start time, which originally existed on the standard physical timeline.

[0031] This involves mapping the start time of the plan to a virtual timeline. The virtual timeline, once constructed, can serve as a new time reference system, and these key nodes are the time positions mapped onto this new system.

[0032] It is the set of all these mapped key time points. In short, the purpose of the above formula is to mark the start times of several key tasks in the first job plan on the virtual timeline, as anchor points or reference points for subsequent scheduling and control.

[0033] The set of critical operational steps is a group of operational tasks selected as having core scheduling significance within the entire first operational plan. These steps have the following characteristics: Resource traction: Its start or completion often affects multiple subsequent operational resources (quay cranes, container trucks); Path constraints: Located on the critical path of port operations, they are the main links that determine the overall operation cycle; Sensitivity to change: It is easily affected by external environmental factors such as tides, water depth, and wind speed; Scheduling node nature: Suitable as a trigger point for scheduling systems to determine whether to adjust the plan.

[0034] Typical key operational steps include the following: Vessel berthing: the starting point for all subsequent operations, dependent on conditions such as tides and water depth; Hoist crane installation begins: This marks the start of the hoisting operation, requiring coordination of multiple pieces of equipment and personnel. The arrival of the first container truck for handover signifies the start of the transportation corridor, requiring coordination with roads and the dispatching system. Yard receiving / delivery start: Yard equipment begins to receive unloaded containers or prepare containers for delivery, affecting the efficiency of the connection between the yard and the horizontal transport system; Vessel departure completed: This indicates that the entire operation is finished, the vessel departs from the dock, and the end of the entire operation cycle.

[0035] S2. Time Axis Deformation Correction: Obtain forecast tidal data and forecast meteorological data for future operation periods; mark effective operation time windows on the virtual time axis based on the forecast tidal data; correct the time flow velocity within the effective operation time window based on the forecast meteorological data to generate a deformed time axis, wherein the time flow velocity is positively correlated with the work environment friendliness.

[0036] S21, by connecting to the port data source interface, obtains information with time-granularity matching characteristics for future operation periods: S211, Tide Forecast Curve: A function representing the relationship between time and tide height, denoted as: Tidal forecast curve It is a time The function mapping to tide height is defined within the work time interval. The output is a non-negative real number, representing the tide level at the corresponding moment. Indicates time The tide height at any given time is provided by tidal forecast data. This refers to the physical time interval corresponding to the virtual time axis, i.e., the start and end times of the first job plan. Let represent the set of non-negative real numbers, and let represent the numerical range of tide height. S212, Weather Forecast Curve: A time series set of meteorological elements including wind speed, precipitation, and visibility, denoted as: .

[0037] S22, Extract the effective operating time window: Based on tidal levels and safe navigation requirements, set: Safe water depth in the channel: ; Ship draft: ; Safety margin: ; The tide height must meet the following conditions: ; The consecutive time periods that meet the above conditions constitute the effective work time window: This formula means: within a given work time interval Inside, find all tide heights. The time points at which safe working conditions are met are grouped together and denoted as the effective working time window. And will Mapped to the virtual timeline, serving as a reference interval for subsequent transformation operations.

[0038] S23, Calculate the time-flow velocity coefficient: Set a preset meteorological-efficiency mapping function. This function converts meteorological elements into a time flow velocity coefficient that reflects operational efficiency. The definition is as follows: ; in, And it satisfies the following trend relationship: ; ; ; That is, the lower the wind speed, the less precipitation, the higher the visibility, the more environmentally friendly the working environment (the higher the environmental friendliness), and the faster the time flow.

[0039] Weather-efficiency mapping function The structure is as follows: The goal is to determine the environmental friendliness of the current operational environment based on real-time meteorological factors (wind speed, precipitation, visibility) and map it to a flow velocity coefficient with time-axis distortion. Its value ranges from (0,1], representing how fast or slow time is at that moment: The environment is excellent, the work efficiency is high, and time can be seen to pass by more quickly. The environment is harsh, work efficiency is low, and time seems to slow down.

[0040] The virtual timeline is used to assist in scheduling calculations, and its elapsed speed represents the speed at which the job progresses.

[0041] High work efficiency, time "accelerated": When work efficiency is high, more tasks can be completed per unit of time. The scheduling system wants to move forward as quickly as possible, so the corresponding time period on the virtual timeline will be compressed into a shorter distance, as if time is passing faster.

[0042] Low work efficiency, time "slows down": Low work efficiency means that fewer tasks are completed per unit of time, scheduling resources are limited, the system should slow down the pace of progress, the corresponding virtual time period will be lengthened, as if time is slowing down.

[0043] Time flow velocity coefficient Mapping methods: Step 1: Collect meteorological element data: Let's assume a certain moment... The weather forecasting system provides the following values: Wind speed: ; Rainfall: ; visibility: .

[0044] Step Two: To incorporate the three types of elements into a unified scoring system, they must first be standardized to dimensionless values ​​between [0,1]. Wind speed standardization (lower is better): ; Precipitation standardization (lower is better): ; Visibility standardization (the higher the better): ; in, The maximum permissible wind speed is set. The maximum set precipitation intensity, The maximum reference visibility is set. The standardized results are all within the range of [0,1], and the closer the value is to 1, the more environmentally friendly it is.

[0045] Step 3: Weighted Fusion into Time Flow Velocity Coefficient: The three standardized values ​​are weighted according to their respective weights to obtain the final time flow velocity coefficient. ;in, , where represents the weighting factors corresponding to the three elements, which can be set. , , , indicating that wind speed has a slightly larger impact.

[0046] Mapping example: Suppose at a certain moment The meteorological data are as follows: Wind speed: ; precipitation: ; visibility: ; After standardization: ; ; ; Weight is , ,but: This indicates that under this environment, the work efficiency is 66.5% of the normal level, and the time flow rate on the virtual timeline is also reduced to 66.5% accordingly.

[0047] S24, perform time axis deformation processing for each effective operation time window. Within the time point Time stretching or compression can be performed in the following ways: ; in, This indicates the virtual timeline corresponding to physical time after deformation. Time and location Indicates time The time-flow velocity coefficient, the integral variable is ,no , It is the traversal time variable in the integration process, representing the time from the starting point to the current point. Each intermediate moment in between represents the rate of time flow at each intermediate moment s, and It only indicates the flow rate of time "at this moment" and cannot be used for cumulative calculations over the entire interval. The indicator function represents the effective job time window, indicating whether to deform the time point (1 inside the window, 0 outside). The deformation time axis is... The non-uniformly changing trajectory over time is used for subsequent scheduling recalculation.

[0048] The core idea of ​​S24 is to dynamically adjust the ebb speed of the time axis by calculating the operation efficiency at different time points, and construct a "deformed time axis" that can truly reflect the feasibility of the operation, so as to guide subsequent collaborative scheduling.

[0049] Within the defined effective operating time window, the operating environment (wind speed, precipitation, visibility) at each time point is converted into a time-flow velocity coefficient, i.e. This coefficient represents the operational efficiency at that moment—the higher the efficiency, the faster time flows; the lower the efficiency, the slower time flows. To construct a timeline reflecting this change in efficiency, an integration mechanism is introduced: starting from the beginning of the virtual timeline, the unit time at each point in time is multiplied by its corresponding efficiency coefficient. The calculation accumulates all these "weighted times," resulting in faster accumulation during high-efficiency periods and slower accumulation during low-efficiency periods. Simultaneously, to avoid interference from invalid areas, only time points within the effective operating time window are calculated. This is controlled by an "indicator function": a value of 1 within the effective window and 0 at other times, meaning only those time points with "high tide targets" are calculated. Finally, the calculation results... This represents "the position of physical time point t on the virtual time axis after efficiency weighting", forming a non-uniform time curve, also known as the "deformed time axis".

[0050] Actual port operations are not consistently efficient throughout the day. For example, multiple lifting operations can be completed in a good hour, but may be impossible in a bad hour. If a uniform timeline is used, the scheduling algorithm will fail to recognize that certain time periods are more valuable. Transforming operational efficiency into timeline deformation is a very intuitive and computationally friendly approach. Compressing efficient phases and lengthening inefficient phases facilitates subsequent task sorting, resource scheduling, and path derivation. Using integral operations instead of discrete addition results in a smoother timeline construction, suitable for modeling continuous-time scheduling and facilitating integration with subsequent fine-tuning and rolling optimization mechanisms. Integral calculations are only performed on time periods where the tide level meets the requirements, ensuring that the timeline only advances within truly workable windows and avoiding the inadvertent inclusion of unavailable time periods in the scheduling scope.

[0051] S3. Generate a collaborative scheduling scheme based on the deformed time axis: On the deformed time axis, recalculate the start time and duration of each operation link, and deduce the collaborative operation instruction sequence of ships, quay cranes, container trucks and yard equipment in reverse to form the final scheduling scheme.

[0052] S31, Determine the critical path anchor point: Set an effective operation time window on the deformation time axis. The endpoint of the last consecutive interval is: This formula represents the effective operating time window that meets all tidal conditions. Within this framework, the latest point in time on the deformation timeline is identified as the final anchorage time at which the ship must complete its operations and depart from port; among which, For the deformation time axis corresponding to physical time Location, The final anchorage time at which a ship must depart is the starting point for the reverse calculation of the scheduling chain.

[0053] S32, Reverse spacetime extrapolation calculation: S321, Calculation of Stoppage Time for Loading and Unloading: Assume the preparation time required for the ship to depart is... The physical time for stopping loading and unloading is: ;in, For the deformation time axis The corresponding physical time, The time required for preparing a vessel for departure includes unmooring, starting the main engine, and pilotage. This is the cutoff time for loading and unloading operations on the quay crane.

[0054] S322, Calculation of the start time of quay crane operation: Assume the total number of containers to be loaded and unloaded is... The efficiency of quay crane operations is determined by the speed of time flow. The number of work boxes per unit time is dynamically determined and defined as follows: ; This represents the actual quay crane operation efficiency at time point t; The actual total required quay crane operation time for: ; Solving for: ; The above integral means that the cumulative efficiency of the quay crane at each moment from the start time to the end time is just enough to complete the total task. Then, the required operation time is calculated based on the cumulative efficiency. To further determine the start time of the quay crane operation; among them, This represents the baseline efficiency (boxes / hour) of the quay crane under standard conditions. This is a time-flow velocity coefficient, which can also represent the friendliness of the working environment. This represents the total operating time of the quay crane, calculated dynamically. Indicates the start time (physical time) of the quay crane operation. This is the end time (physical time) of the quay crane operation, usually the loading and unloading cut-off point.

[0055] S323, Generation of truck transport routes and time series: Assume the location of each truck in the storage yard is... The quay crane allocation point is On the deformation time axis, according to the traffic efficiency function For the first Round-trip time for ship transport missions: ;in, For the first The location of the Taiwan truck yard is to the first The distance to the Taian Bridge The standard speed for container trucks. For time points The road traffic efficiency coefficient. For the first Time required for one round trip. Indicates the first The first transport mission, namely the The scheduling time point corresponding to the round trip of the second truck is the actual time when the task in this round occurs. Simply put... It is the first The time point for batch truck transportation is used to check the traffic efficiency at that moment. .

[0056] Based on the time sequence of the quay cranes, the departure time, arrival time, and return time of each round of transportation are deduced, forming a time point sequence. .

[0057] S324, Generation of yard crane operation instruction sequence: Based on the above truck arrival time sequence. Generate a matching container retrieval or storage instruction for each yard crane (RTG, RMG): That is, every time a truck arrives or leaves, it triggers a specific yard equipment action, including the time of operation, the target container location, and the type of operation (lifting / dropping container).

[0058] S33, Generate the final scheduling scheme: Integrate all equipment (quay cranes, container trucks, yard cranes) operation instructions according to their corresponding physical time sequence to form a final scheduling instruction sequence for end-to-end coordination: This formula indicates: [Regarding the quay bridge] Operation instructions, container trucks Transportation tasks and yard equipment The operation instructions, after being merged, are arranged according to the corresponding physical time. The instructions are sorted sequentially to generate a unified sequence of scheduling instructions. .in, This represents the set of instructions for quay crane operations. This represents a set of truck transportation tasks. This represents the set of operation instructions for yard equipment. This indicates that the three types of tasks will be combined into one. Indicated by time Sort all instructions.

[0059] QC stands for Quay Crane, a crane used for ship loading and unloading operations, responsible for lifting containers from ships to the dock or back from the dock to the ship. Truck stands for Container Truck, referring to trucks used for horizontal container transport within the port, used to move containers between the quay crane and the container yard. Yard stands for Container Yard or Yard Crane, referring to the container stacking area and its lifting equipment, such as RTG and RMG yard cranes, used to receive or dispatch containers transported by trucks. QC is responsible for lifting at the ship's side, truck for intermediate transport, and yard for container handling. These three constitute a collaborative chain of port operations.

[0060] It should be noted that if the reverse simulation results show that the operation time is insufficient to complete all operation tasks, further optimizations such as operation compression, resource reallocation, or dynamic adjustment of departure anchor points will be implemented. In other words, the current scheme does indeed use "anchor points" as a hard constraint for reverse simulation, but if the feasibility verification fails, a response mechanism must be introduced, such as operation workload compression, resource optimization, or departure time adjustment, to ensure that the entire scheduling system is practical.

[0061] In this invention, all scheduling plans are calculated in reverse with the end time of the tidal window (final anchor point) as a rigid constraint. However, since the deformation time axis is non-uniform, if the quay crane efficiency is low, the truck path is long or the passage efficiency is poor, or the draft requirement is high, resulting in a very short working time window, the total working time required to work backward from the anchor point time may exceed the starting point of the effective working time window, meaning there is not enough time.

[0062] To address this issue, the present invention can introduce the following exception handling and adaptive scheduling mechanism: 1. Dynamic workload reduction mechanism: Determine whether partial unloading / loading is possible, decompose the total loading and unloading tasks into those that can be completed or those that can be delayed, prioritize the parts that can be completed within the window, and postpone the rest to the next tide window, triggering rolling optimization of the plan; reduce the lowest priority operations, such as non-urgent cargo, non-main route vessels, and temporary operation insertions.

[0063] 2. Enhance operational resource coordination: It is recommended to increase the number of quay cranes or the frequency of truck dispatching. If there is insufficient operation time, you can be prompted to temporarily adjust the resource configuration (add a quay crane) to improve efficiency per unit time.

[0064] 3. Dynamic Anchor Point Adjustment Recommendation Mechanism: If the workload cannot be further reduced and resources cannot be adjusted, the theoretically required latest departure time can be calculated in reverse. If this time exceeds the end of the current tide window, then: Try to postpone the vessel's scheduled departure time to the next tidal window; Alternatively, the dispatcher can be notified to coordinate manually.

[0065] S4. Dynamic maintenance of the time axis: During the operation, the deformed time axis is dynamically adjusted according to the deviation between real-time tidal and meteorological data and forecast values, and the rolling optimization of the final scheduling scheme is triggered.

[0066] S41 continuously receives real-time data streams during job execution, including: Real-time tidal curve: ; Real-time weather curves: ; And calculate the deviation from the forecast data used in S2: ; ; in, This represents the instantaneous deviation of the corresponding element.

[0067] S42, set a trigger threshold for each type of deviation: ; If any of the above deviations continues to exceed the corresponding threshold, the minimum trigger duration will be reached. This triggers scroll optimization, as shown below: This formula means: at the current time point In the next period of time If there exists a certain moment within... The deviation of a certain monitored quantity (tide height, wind speed, precipitation or visibility) Continuously exceeding its corresponding deviation threshold If this occurs, an update or reconstruction operation on the deformation timeline will be triggered, with a minimum trigger duration. Set to a multiple of the update time for meteorological and tidal data. If the deviation continues to exceed multiple update times, it indicates that it is not a short-term error but a trend deviation, and scheduling adjustments should be triggered immediately.

[0068] in, These are all deviation thresholds (namely: tide height deviation threshold, wind speed deviation threshold, precipitation intensity deviation threshold, and visibility deviation threshold). For the required duration of deviation, This represents the set of dimensions for deviation monitoring.

[0069] The recommended threshold for tidal height deviation is ±0.10m. Based on the port's draft margin, a deviation of 10cm has already affected the judgment of berthing or departure, and correction needs to be triggered in advance.

[0070] The wind speed deviation threshold is recommended to be ±2m / s. Equipment such as quay cranes and yard cranes need to reduce speed or stop operating in wind speeds of 15–20m / s. A forecast deviation of 2m / s may lead to incorrect judgment of the operational status.

[0071] The recommended threshold for precipitation intensity deviation is ±2 mm / h. Ports often use ≥5 mm / h to determine moderate rain. A deviation of 2 mm / h between forecast and actual rainfall can turn "no rain" into "moderate rain," directly affecting the efficiency of storage yards and transportation.

[0072] The visibility deviation threshold is recommended to be ±150m. Truck scheduling and autonomous driving usually require visibility of ≥500m. An error of 150m may cause some routes to change from "passable" to "inaccessible".

[0073] S43, Dynamic adjustment of the deformation timeline shape: S431, Local Deformation: If the deviation occurs within the current work window, i.e. In this case, only the local area in the deformation timeline will be updated and corrected. ; ; This represents the time-velocity coefficient recalculated based on real-time meteorological data. This indicates the updated deformation timeline.

[0074] S432, Global Reconstruction: If the deviation continues and shows an overall worsening trend in the future, such as predicting continuous strong winds / heavy rain, then discard the original timeline, re-execute step S2, and generate a completely new deformed timeline. That is, using the latest tidal and meteorological data as input, we reconstruct the effective operating time window and a new time flow velocity function.

[0075] S44, regardless of the update Or refactor to All of these are based on re-executing the reverse spatiotemporal deduction process in S3 on the new time axis, and quickly generating a new set of collaborative scheduling instructions.

[0076] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0077] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for tidal and meteorological linkage scheduling for port operation coordination, characterized in that, The method comprises the following steps: S1, taking a first operation plan generated for a ship to be dispatched as a reference, creating a virtual time axis corresponding to a future operation period, and the initial state of the virtual time axis being a standard uniform elapsing time axis; S2, obtaining forecast tide data and forecast weather data for the future operation period; and marking an effective operation time window on the virtual time axis according to the forecast tide data; According to the forecast weather data, the time flow speed in the effective operation time window is corrected to generate a deformed time axis, wherein the time flow speed is positively correlated with the operation environment friendliness; S3, on the deformed time axis, the starting time point and the duration of each operation link are recalculated, and the coordinated operation instruction sequence of the ship, the shore crane, the truck and the yard equipment is reversely derived to form a final scheduling scheme; S4, in the operation execution process, the deformed time axis is dynamically adjusted according to the deviation of the real-time tide and weather data from the forecast values, and the rolling optimization of the final scheduling scheme is triggered.

2. The tide and weather linkage scheduling method for port operation coordination according to claim 1, characterized in that, The S1 comprises determining a starting time point and an ending time point of the virtual time axis, wherein the starting time point is the planned start time of the earliest operation link in the first operation plan, and the ending time point is the planned end time of the latest operation link.

3. The method of claim 1, wherein, The S1 further comprises initializing the virtual time axis to uniformly elapse at a standard physical time rate between the starting time point and the ending time point, and marking the initial time nodes corresponding to the key operation links in the first operation plan.

4. The method of claim 1, wherein, The obtaining of the forecast tide data and the forecast weather data for the future operation period specifically comprises obtaining time-matched tide forecast curves and weather forecast curves within the future operation period from a port data source interface, extracting a continuous time period in which the tide height satisfies the safe operation condition from the tide forecast curves according to the water depth of the port channel and the draft depth of the ship, and mapping the continuous time period to the virtual time axis to be marked as the effective operation time window.

5. The method of claim 1, wherein, The S2 comprises converting the element values in the weather forecast curve into corresponding time flow speed coefficients in real time based on a preset weather-efficiency mapping function, wherein the lower the wind speed, the smaller the precipitation, and the higher the visibility, the closer the time flow speed coefficient is to 1, indicating that the time elapses faster and the operation efficiency is higher; otherwise, the time flow speed coefficient tends to 0, indicating that the time elapses slower and the operation efficiency is lower.

6. The method of claim 5, wherein, The S2 further comprises multiplying each physical time unit within the effective operation time window by the corresponding time flow speed coefficient, thereby stretching or compressing the uniformly elapsing physical time axis, specifically comprising weighting and integrating the physical time based on the time flow speed coefficient of each time point within the effective operation time window to generate a deformed time axis; the time position of the deformed time axis at any physical time point t is determined by the integral of the time flow speed from the starting point of the virtual time axis to the time point t, and only the time period within the effective operation time window is accumulated and corrected to build a non-uniform deformed time axis reflecting the change of operation efficiency.

7. The method of claim 1, wherein, The S3 includes the end point of the last valid job time window marked on the transformed time axis as the final anchoring point time when the ship must leave the port, and performs reverse space-time deduction from the final anchoring point time to perform reverse deduction calculation on the transformed time axis.

8. The method of claim 7, wherein, The reverse deduction calculation specifically includes: a. According to the standard time consumption of the ship's departure operation, calculate the stop loading and unloading time point; b. According to the actual time flow speed corresponding to the stop loading and unloading time point on the transformed time axis and the total amount of goods to be loaded and unloaded, calculate the total length of the required shore crane operation, and determine the starting time point of the shore crane operation; c. Based on the shore crane operation time sequence, the yard location and the traffic efficiency on the transformed time axis, assign a transport batch and path to each truck, and calculate the sequence of its round trip time points between the yard and the shore crane; d. According to the arrival time sequence of the truck, generate a corresponding yard box picking or storing operation instruction sequence for the yard crane equipment; e. Sort and integrate all device operation instructions obtained by reverse deduction calculation according to their corresponding physical time points to form the final scheduling scheme.

9. The port operation collaboration oriented tidal and meteorological linkage scheduling method according to claim 1, characterized in that, In the S4: During operation, continuously access real-time tidal and meteorological data streams, and calculate the deviation value between them and the corresponding predicted tidal data and predicted meteorological data used in S2, set trigger thresholds for tidal height deviation and various meteorological element deviations; When the absolute value of any deviation value continuously exceeds its corresponding trigger threshold and reaches a preset length of time, dynamically adjust the transformed time axis, and immediately trigger the rolling optimization process, automatically re-execute the reverse deduction in S3 based on the updated or completely new transformed time axis, generate a new sequence of coordinated operation instructions, and immediately issue the updated instructions to the affected operation equipment.

10. The method of claim 9, wherein, The dynamic adjustment of the transformed time axis specifically includes: a. Local deformation: If the deviation occurs in the current or upcoming operation period, the time flow speed of the corresponding local section of the transformed time axis is immediately corrected according to the real-time data to generate an updated transformed time axis; b. Global reconstruction: If the deviation indicates that there will be a major change in future environmental trends, discard the original time sequence, input the latest prediction data, re-execute S2, and construct a completely new transformed time axis.

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