Regulation and control method based on port supply chain platform

Abstract

The embodiment of the invention provides a regulation and control method based on a port supply chain platform, and the method comprises the steps: obtaining the real-time meteorological data of a port, and predicting the influence range and duration of severe weather according to the meteorological data; based on the predicted severe weather information, adjusting the priority order of the cargos in the port; a cargo scheduling plan is dynamically updated through a port supply chain platform so as to reduce cargo retention and delay; and a port inventory management strategy is optimized, and reasonable utilization and quick response of the warehouse during severe weather are ensured. Through the scheme of the embodiment of the invention, the problem of inventory management and scheduling conflict caused by cargo retention and delay under the influence of severe weather can be solved.

Description

Technical Field

[0001] The present application relates to the technical field of port supply chain management, and in particular to a control method based on a port supply chain platform. Background Art

[0002] Port control aims to improve logistics efficiency and reduce operating costs by integrating information technology and intelligent algorithms to optimize the collaboration and scheduling of all links in the port supply chain. However, in severe weather conditions, the impact on port operations often leads to cargo detention and delays, which in turn causes conflicts between inventory management and scheduling. For example, delayed arrival of goods may cause warehouses to be overloaded, and the scheduled transportation plan cannot be executed on time, ultimately affecting the smooth operation of the entire supply chain. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure provide a control method based on a port supply chain platform, which at least partially solves the problems existing in the prior art.

[0004] A control method based on a port supply chain platform of the present application includes: Obtaining real-time weather data of the port and predicting the impact range and duration of severe weather based on the weather data; Adjust the priority sorting of cargo within the port based on predicted severe weather information; Dynamically update cargo dispatch plans through the port supply chain platform to reduce cargo detention and delays; Optimize port inventory management strategies to ensure rational utilization and rapid response of warehouses during severe weather.

[0005] Preferably, adjusting the priority order of cargo in the port based on the predicted severe weather information includes: Get real-time weather data and forecast severe weather intensity level G; Cargo in the port is divided into three categories according to the predicted intensity level G: high priority, medium priority and low priority; If the predicted intensity level G > T1, the susceptible goods are classified as high priority, and other goods are classified as medium priority and low priority in sequence; Dynamically adjust cargo dispatch plans and give priority to high-priority cargo to reduce cargo detention and delays.

[0006] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Collect basic information of each shipment, including weight W, volume V and value P; Calculate the risk index R of each cargo, risk index R = (W + V + P) / 3; If the predicted duration of bad weather D > T2, where T2 is a preset threshold, the priority of cargo with a risk index R above a certain threshold R > T3 is increased, where T3 is a preset threshold; Update dispatch plans to prioritize cargo with high risk indices.

[0007] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Get the loading and unloading time Ti and transportation time Ti of each cargo; Calculate the total time for the goods Ti_total = Ti + Ti; If the predicted bad weather duration D > T2 and the total time Ti_total > T4, where T4 is the preset threshold, the priority of the cargo is increased; Update the dispatch plan to give priority to shipments with the longest total processing time.

[0008] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Get the information of the destination city Ci of the goods; Calculate the average distance D_average from the destination city Ci to the current port; If the predicted severe weather impact range W_influence covers the target city Ci and the average distance D_average > T5, where T5 is the preset threshold, the priority of the cargo is increased; Update dispatch plans to prioritize shipments that are transported over long distances.

[0009] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Get the value fluctuation coefficient V_fluc of each commodity; Calculate the value change rate of each cargo C_rate = (V_end-V_start) / V_start, where V_end and V_start are the estimated value after reaching the destination and the current value respectively; If the predicted severe weather intensity G > T6, T6 is the preset threshold, and the value change rate C_rate < T7, T7 is the preset threshold, then the priority of the cargo is lowered; Update dispatch plans to prioritize shipments with high value fluctuations.

[0010] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Get the storage time T_store of each product; Calculate the storage cost F_cost = K × T_store, where K is the storage cost per unit time; If the predicted duration of bad weather D > T8, T8 is the preset threshold, and the storage cost F_cost > T9, T9 is the preset threshold, the goods with longer storage time will be processed first; Update scheduling plans to reduce warehouse storage pressure.

[0011] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Get the transportation distance D_transport of each cargo; Calculate the transport cost T_cost = C1 × D_transport + C2, where C1 is the fixed transport cost per kilometer and C2 is the additional fixed cost of transport; If the predicted bad weather duration D > T10, T10 is the preset threshold, and the transportation cost T_cost > T11, T11 is the preset threshold, the goods with high transportation cost are processed first; Update dispatch plans to optimize transportation costs.

[0012] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Get the importance of each cargo I_importance; Calculate the importance factor A_factor = I_importance / T12, where T12 is the preset importance threshold; If the predicted severe weather impact range W_influence covers the critical transportation path and the importance impact factor A_factor > T13, where T13 is the preset threshold, the priority of important goods will be increased; Update dispatch plans to ensure timely delivery of important shipments.

[0013] Preferably, adjusting the priority order of cargoes in the port based on the predicted severe weather information further comprises: Get the urgency of each cargo E_urgency; Calculate the urgency weight E_weight = E_urgency / W_warehouse, where W_warehouse is the maximum capacity of the warehouse; If the predicted severe weather intensity G > T14, T14 is the preset threshold, and the urgency weight E_weight > T15, T15 is the preset threshold, the cargo with high urgency will be processed first; Update dispatch plans to reduce cargo delays.

[0014] The disclosed embodiment provides a control method based on a port supply chain platform, including: obtaining real-time meteorological data of the port, and predicting the impact range and duration of bad weather according to the meteorological data; adjusting the priority sorting of goods in the port based on the predicted bad weather information; dynamically updating the cargo scheduling plan through the port supply chain platform to reduce cargo detention and delays; optimizing the port inventory management strategy to ensure the rational use and rapid response of warehouses during bad weather. Through the solution of the disclosed embodiment, the inventory management and scheduling conflict problem caused by cargo detention and delays under the influence of bad weather can be solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in the present application and should not be regarded as limiting the scope of the present application.

[0016] Figure 1 It is a flow chart of a control method based on a port supply chain platform; Figure 2 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to the first embodiment of the present application; Figure 3 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a second embodiment of the present application; Figure 4 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a third embodiment of the present application; Figure 5 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a fourth embodiment of the present application; Figure 6 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a fifth embodiment of the present application; Figure 7 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a sixth embodiment of the present application; Figure 8 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to the seventh embodiment of the present application; Fig. 9 is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to an eighth embodiment of the present application; Fig.10is a flowchart of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a ninth embodiment of the present application; Fig.11 It is a block diagram of the control system based on the port supply chain platform of this application. DETAILED DESCRIPTION

[0017] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0018] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0019] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0020] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The drawings only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0021] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0022] Next, refer to Figure 1, describing a control method based on a port supply chain platform of the present invention and how it solves the inventory management and scheduling conflicts caused by cargo detention and delays under the influence of severe weather.

[0023] S101: Acquire real-time weather data of the port, and predict the impact range and duration of severe weather according to the weather data; S102: Adjust the priority sorting of cargo in the port based on the predicted severe weather information; S103: Dynamically update cargo dispatch plans through the port supply chain platform to reduce cargo detention and delays; S104: Optimize port inventory management strategies to ensure rational utilization and rapid response of warehouses during severe weather.

[0024] First, the method includes obtaining real-time meteorological data of the port and predicting the impact range and duration of severe weather based on these data. Real-time meteorological data is usually obtained through meteorological stations installed in and around the port and satellite data. These data not only contain information such as current temperature, humidity, wind speed, etc., but also include weather forecasts for a period of time in the future. Through data analysis and model prediction, the system can estimate the specific impact of severe weather on port operations, such as which areas will be affected and how long the impact will last. For example, in one embodiment, the system predicts that a strong typhoon will land within 48 hours and will stay in the port area for about 12 hours, causing the loading and unloading operations to be suspended.

[0025] Based on the predicted severe weather information, adjusting the priority of cargo within the port is the next step. Specifically, according to the degree and duration of the severe weather's impact on different areas of the port, the system will prioritize those cargoes that are vulnerable to weather and time-sensitive. Prioritization can be determined by a variety of factors, such as delivery time, cargo type, customer importance, etc. For example, in the case of an impending typhoon, the system will prioritize the loading and unloading and transportation of cargoes that have arrived at the port's terminals with better weather conditions to avoid these cargoes being stranded in high-risk areas during the typhoon. In addition, for cargoes that need to be delivered urgently and are time-sensitive, inland logistics providers can be notified in advance to prepare for the response to reduce delays.

[0026] Dynamically updating cargo dispatch plans through the port supply chain platform is to solve the problem of cargo detention and delays caused by bad weather. The platform will adjust the loading and unloading plans of various goods in real time according to the latest weather forecast information to minimize losses. The dispatch plan not only involves operations within the port, but also includes coordination with inland logistics, warehousing and other related links. For example, when it is predicted that a certain area may be shut down due to a storm, the system will immediately adjust the work tasks of other nearby areas, rearrange the ship berthing schedule and land transportation routes, and ensure the continuity and effectiveness of the logistics chain.

[0027] Optimizing the port inventory management strategy is a key measure to ensure the rational use and rapid response of warehouses during severe weather. Through a comprehensive assessment and reallocation of existing storage resources, waste of warehouse space or excessive congestion can be avoided. For example, when strong winds or heavy rains cause the port to be temporarily closed, the system will guide staff to prioritize the storage of unloaded goods in sheltered and well-ventilated warehouses, and try to stay away from low-lying areas that may be flooded. In addition, in order to meet the needs of rapid allocation of goods in emergency situations, temporary transfer stations can be set up in key areas to shorten logistics response time. Through the above steps, the control method based on the port supply chain platform effectively alleviates the negative impact of severe weather and improves the resilience and flexibility of the entire supply chain.

[0028] Next, refer to Figure 2-Figure 10 , describing the second to ninth embodiments of the present application for adjusting the priority sorting of cargo in a port based on predicted severe weather information, and Figure 2 Corresponding to the first embodiment, Figure 3 The corresponding second embodiment and so on. In addition, it should also be understood that the solutions of these embodiments can be separated or combined to form a new technical solution.

[0029] First, refer to Figure 2 , describing the specific steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to the first embodiment of the present invention.

[0030] S201: Acquire real-time meteorological data and predict the intensity level G of severe weather. This step collects real-time meteorological data from multiple data sources (such as satellite images, ground observation stations, etc.) by using meteorological monitoring equipment and data analysis algorithms. After analysis and modeling, it predicts the severe weather that may occur near the port in the future and quantifies it into an intensity level G. For example, if the meteorological data shows that a strong typhoon is approaching in the next few days, the intensity level G may be rated as 3 or 4. Various existing methods can be used to obtain real-time meteorological data and predict severe weather, which will not be repeated here.

[0031] S202: Classify the cargo in the port into three categories according to the predicted intensity level G: high priority, medium priority and low priority. In this step, the predicted weather intensity level is used to determine which cargo may be severely affected by bad weather, and then prioritize them. For example, when G=3, cargo such as paper and chemicals that may be damaged by rain are classified as high priority; cargo such as metal products that are more weather-resistant are classified as medium priority; and cargo such as ceramics and glass that are not easily affected by weather are classified as low priority.

[0032] S203: If the forecast intensity level G > T1, the vulnerable goods are classified as high priority, and other goods are classified as medium priority and low priority in turn. Here, T1 is a threshold, usually set to 2, used to distinguish whether it is necessary to start the priority adjustment plan. The specific value of T1 can be determined based on historical data and experience, and its value range is generally between 1 and 3. For example, in one embodiment, if the weather forecast shows G=4, which is much greater than T1=2, the emergency plan is immediately activated to give priority to all vulnerable goods to avoid potential losses.

[0033] S204: Dynamically adjust the cargo dispatch plan and give priority to high-priority cargo to reduce cargo detention and delays. In this step, the system will update and optimize the cargo dispatch plan in real time, and give priority to the loading, unloading, and transshipment of high-priority cargo. For example, after a storm warning, the dispatch system quickly transfers all paper cargo stored in open-air warehouses to indoor storage, and gives priority to completing the loading tasks of these cargoes to ensure their safe and timely departure.

[0034] Throughout the entire process, by analyzing and managing the predicted severe weather information, this method effectively improves the port's ability to respond to emergencies and ensures the stable operation of the supply chain.

[0035] Next, refer to Figure 3 , describing the steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a second embodiment of the present invention.

[0036] S301: Collect basic information of each cargo, including weight W, volume V and value P; S302: Calculate the risk index R of each cargo, where the risk index R = (W + V + P) / 3; S303: If the predicted duration of bad weather D > T2, where T2 is a preset threshold, increase the priority of goods with a risk index R higher than a certain threshold R > T3, where T3 is a preset threshold; S304: Update the dispatch plan and give priority to goods with high risk index.

[0037] First, the system needs to collect basic information about each cargo, including the cargo's weight W, volume V, and value P. The weight W here represents the mass of the cargo, usually in tons; the volume V represents the physical size of the cargo, usually in cubic meters; and the value P refers to the economic value of the cargo, usually in monetary terms. These parameters have clear meanings and dimensions in specific calculations.

[0038] Secondly, calculate the risk index R of each cargo. The calculation method is to add the weight W, volume V and value P of each cargo and divide it by 3, that is, R = (W + V + P) / 3. The original intention of this formula is to comprehensively evaluate the risk of cargo in bad weather, where W, V and P reflect the difficulty of transportation and potential losses of cargo from different perspectives. For example, a heavy and bulky cargo is more likely to be damaged during transportation, while a high-value cargo faces higher economic risks. Through this balanced approach, the comprehensive risk index R of each cargo can be more reasonably evaluated.

[0039] If the predicted duration of bad weather D exceeds the preset threshold T2, the system will further adjust the priority of the goods. Here, T2 is a pre-set time threshold used to determine the severity of bad weather. Typically, T2 may be set to a few hours to a whole day, depending on the actual needs of the port and historical experience. When D > T2, it means that the predicted bad weather is more severe and more attention needs to be paid to goods with a high risk index. At this time, the system will increase the priority of goods whose risk index R is higher than another preset threshold T3. T3 is another pre-set threshold used to screen out the highest risk goods, usually set in the higher range of the risk index R. For example, if T3 is set to 8.0 (assuming the maximum value of R is 10.0), only those goods with R > 8.0 will be considered high-risk goods and need to be given priority.

[0040] Finally, the system updates the scheduling plan and puts the cargo with a high risk index in front. This step is to ensure that the processing of high-risk cargo is completed before the bad weather arrives to reduce potential losses. Specifically, this may involve practical operations such as rearranging the berthing order of cargo ships and adjusting the use priority of loading and unloading equipment. For example, in one embodiment, suppose there is a container with W = 10 tons, V = 20 cubic meters, P = 1 million yuan, and the calculated risk index R = (10+ 20 + 100) / 3 ≈ 43.33. If T2 is set to 6 hours, the predicted duration of bad weather is 10 hours, and T3 is set to 40, then this container will be prioritized due to its high risk index.

[0041] The above steps can effectively protect the safety of cargo at the port and reduce economic losses when severe weather comes by reasonably evaluating and prioritizing high-risk cargo.

[0042] Next, refer to Figure 4 , describing the steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information in a third embodiment of the present invention.

[0043] S401: Obtain the loading and unloading time Ti and transportation time Ti of each cargo; S402: Calculate the total time of the goods Ti_total = Ti + Ti; S403: If the predicted bad weather duration D > T2 and the total time Ti_total > T4, where T4 is a preset threshold, the priority of the cargo is increased; S404: Update the dispatch plan and give priority to the goods with the longest total processing time.

[0044] Obtaining the loading and unloading time Ti and transportation time Ti for each cargo is the starting point of the whole process. The loading and unloading time Ti refers to the time required from the arrival of the cargo at the port to the completion of the loading and unloading operation, while the transportation time Ti refers to the time between the completion of loading and unloading and the actual start of transportation. These two times are usually obtained from historical data statistics, and their units are hours, generally ranging from 1 to 24 hours. The optimal value depends on the specific cargo type and the port's operating efficiency.

[0045] Calculate the total time of the cargo Ti_total = Ti + Ti, which is the sum of the loading and unloading time and the transportation time. This formula is designed to comprehensively evaluate the processing cycle of each cargo throughout the port. By combining two independent time variables into a comprehensive indicator, the potential risk of each cargo in bad weather can be more accurately measured, providing a scientific basis for subsequent priority adjustments.

[0046] If the predicted duration of bad weather D > T2 and the total time Ti_total > T4, where T4 is a preset threshold, the priority of the cargo is increased. Here, T2 is a benchmark value pre-set by the port, usually set to about 6 hours, which is used to determine whether the upcoming bad weather will have a significant impact on port operations; T4 is a safety threshold used to identify those cargoes that are most vulnerable during the expected bad weather. When the predicted duration of bad weather exceeds this benchmark value T2, it means that the future environment will deteriorate significantly; and if the total processing time of the cargo also exceeds the threshold T4, then such cargo should be given a higher priority to speed up the unloading or transportation process.

[0047] Update the scheduling plan to give priority to cargoes with a long total processing time. This final step ensures the efficient allocation of port resources. After confirming that the priority of certain cargoes needs to be increased, the port management will adjust the existing operation plan so that these high-priority cargoes can be processed before the bad weather, minimizing the impact of bad weather. For example, in one embodiment, suppose that the port receives a forecast from the meteorological department about a strong typhoon, with a predicted duration of 72 hours. At this time, the port staff used the aforementioned method to evaluate the loading and unloading time and transportation time of a batch of cargo, and found that the total processing time of one of the high-value chemical raw material batches was 30 hours, which obviously exceeded the preset safety threshold. Therefore, the dispatcher immediately rearranged the plan and put the batch of materials on the first processing list to avoid the risk of possible flooding losses.

[0048] Next, refer to Figure 5 , describing the steps of adjusting the priority sorting of cargoes in a port based on predicted severe weather information according to a fourth embodiment of the present invention.

[0049] S501: Obtain the information of the destination city Ci of the goods; S502: Calculate the average distance D_average from the destination city Ci to the current port; S503: If the predicted bad weather impact range W_influence covers the target city Ci and the average distance D_average > T5, where T5 is a preset threshold, the priority of the cargo is increased; S504: Update the dispatch plan to give priority to goods transported over long distances.

[0050] First, the system obtains information about the destination city Ci of the goods. The purpose of this step is to understand the final destination of each cargo to determine the impact that bad weather may have on it. The climatic conditions and geographical environment of the destination city directly affect the transportation safety of the goods. For example, if the final destination of a certain cargo is in a rainy tropical area, and the rainfall surges during bad weather, this information is of great reference value for subsequent decision-making.

[0051] Next, calculate the average distance D_average from the destination city Ci to the current port. Here, D_average is the average straight-line distance or actual road distance obtained based on historical data and actual map information, which aims to measure the transportation distance of each cargo. The specific calculation method of the average distance is to average the distances of multiple possible paths between the starting point and the end point, and the value range is usually between tens of kilometers and thousands of kilometers. The significance of this step is to identify those cargoes that need to be handled as a priority by quantifying the transportation distance to ensure that the port operation efficiency is maximized within a limited time. In one embodiment, if the average transportation distance of a shipment is 3,000 kilometers, it obviously belongs to the long-distance transportation category.

[0052] Then, check whether the predicted bad weather impact range W_influence covers the target city Ci. If the answer is yes, and D_average is greater than the preset threshold T5, the system will increase the priority of the cargo. T5 is a pre-set critical value used to distinguish which cargoes need to be given priority. For example, T5 can be set to 1000 kilometers. The selection of this threshold is based on the actual situation of the port and the transportation chain, as well as an estimate of the impact range of bad weather. Under this condition, cargo with D_average > T5 is considered more urgent and needs to be loaded and departed first. In a specific embodiment, if the weather forecast shows that a strong typhoon will occur in a coastal city in the next 48 hours, and the distance of a cargo shipped to the city exceeds 1500 kilometers, the cargo will be given priority to avoid transportation delays or cargo damage caused by the typhoon.

[0053] Finally, the dispatch plan is updated to prioritize goods that are transported over long distances. This step is to ensure that high-priority goods can be shipped on time, thereby reducing overall logistics costs and improving customer satisfaction. At a port, if the system finds that there are multiple shipments that meet the above conditions, they will be arranged from small to large according to their D_average, and prioritized for loading and transportation. Specifically, if there are multiple shipments with transportation distances of 2,000 km, 3,500 km, and 800 km, the shipments of 3,500 km and 2,000 km will be processed first. This can not only effectively cope with the impact of bad weather, but also ensure the overall stability and reliability of the supply chain.

[0054] Next, refer to Figure 6 , describing the steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a fifth embodiment of the present invention.

[0055] S601: Obtain the value fluctuation coefficient V_fluc of each commodity; S602: Calculate the value change rate C_rate of each cargo, where C_rate = (V_end - V_start) / V_start, and V_end and V_start are the value after expected arrival at the destination and the current value respectively; S603: If the predicted severe weather intensity G > T6 (T6 is a preset threshold) and the value change rate C_rate < T7 (T7 is a preset threshold), then reduce the priority of this cargo; S604: Update the scheduling plan and prioritize the handling of cargos with large value fluctuations.

[0056] This method first needs to obtain the value fluctuation coefficient V_fluc of each cargo. The value fluctuation coefficient of a cargo is an indicator reflecting the degree of value change of the cargo during transportation, usually ranging from 0 to 1. The closer the value is to 1, the greater the impact of external factors on the value of the cargo. For example, some perishable goods or high-value technology products may have a relatively high fluctuation coefficient.

[0057] Next, calculate the value change rate C_rate of each cargo, where C_rate = (V_end - V_start) / V_start, and V_end and V_start are the value after the cargo is expected to arrive at the destination and the current value respectively. This formula is used to evaluate the change ratio of the cargo's value compared to the current value after arriving at the destination. If V_end is greater than V_start, it means the value of the cargo will increase; otherwise, it means the value will decrease. For example, the demand for some seasonal products may increase during a specific period, thus increasing their terminal value.

[0058] Then, determine whether to reduce the priority of the cargo based on whether the predicted severe weather intensity G exceeds the preset threshold T6 and whether the value change rate C_rate of the cargo is less than the preset threshold T7. The preset threshold T6 is usually set based on historical data and the advice of meteorological experts and is used to judge whether the weather is severe enough to have a significant impact on port operations. Generally, it ranges from 1 to 10. For example, 6 represents a relatively strong level of storm. The threshold T7 is used to control the sensitivity of the cargo value change and is usually set between 0.1 and 0.2. For example, 0.15 means that the priority needs to be adjusted only when the value change rate of the cargo is less than 15%.

[0059] In one embodiment, assume that the cargo in a container is a high-end electronic device with a value fluctuation coefficient V_fluc of 0.8, which means that this cargo is very susceptible to external factors during transportation. If the weather forecast shows that a storm with an intensity of 8 will affect the port in the next few days, and the estimated value of the cargo after reaching the destination V_end is US$9,500, and the current value V_start is US$10,000, then its value change rate C_rate= (9500-10000) / 1000 = -0.05. Since the severe weather intensity G = 8 > T6 = 6 and the value change rate C_rate= -0.05 < T7 = 0.15, the priority of the cargo needs to be lowered so that those cargoes with larger fluctuations can be processed first.

[0060] In addition, in one embodiment, priority may be given to goods whose value fluctuation coefficient V_fluc is greater than a predetermined threshold.

[0061] Finally, update the scheduling plan to ensure that those goods with high value fluctuations are handled first. Doing so will help minimize the impact of bad weather on port logistics efficiency and reduce potential economic losses. For example, the port scheduling system will rearrange the loading and unloading order to ensure that those goods that are vulnerable and have a higher terminal value are handled first.

[0062] Next, refer to Figure 7 , describing the steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information according to a sixth embodiment of the present invention.

[0063] S701: Obtain the storage time T_store of each cargo. The storage time here refers to the length of time from the cargo entering the warehouse to the present. This information can be obtained through the warehouse management system of the port to ensure the real-time and accuracy of the data. For example, in one embodiment, there are multiple cargoes in the port warehouse, and the system records the specific storage time of each cargo by scanning the QR code or reading the RFID tag.

[0064] S702: Calculate the storage cost F_cost = K × T_store, where K is the storage cost per unit time. K is usually set by the port's management and operation department based on actual costs, and its range is usually from a few dollars to tens of dollars per hour. The optimal value depends on the port's operation strategy and cost structure. The meaning of this formula is to calculate the total storage cost incurred during the storage of a certain cargo in the port, so that the subsequent steps can evaluate whether the cost is too high. In one embodiment, assuming that K is $10 per hour, and a certain cargo has been stored for 20 days (i.e., 480 hours), its storage cost is $4,800.

[0065] S703: If the predicted duration D of bad weather exceeds the preset threshold T8, and the storage cost F_cost exceeds another preset threshold T9, the goods with longer storage time will be given priority. T8 and T9 are set by the port management based on historical experience and specific circumstances. Generally, T8 may be set to a few days (such as 3 days), and T9 may be set to a few thousand dollars (such as 5,000 dollars). The purpose of this conditional judgment is to give priority to goods with long storage time and high storage cost when facing long-term bad weather, so as to reduce the overall operating cost of the port. In a specific example, assuming T8 = 3 days, T9 = 5,000 dollars, the predicted bad weather will last for 5 days. At this time, the aforementioned goods with a storage time of 20 days and a storage cost of 4,800 dollars will meet the conditions and be given priority.

[0066] S704: Update the scheduling plan to reduce warehouse storage pressure. This step means that the system will readjust the order of goods leaving the warehouse to ensure that qualified goods leave the port as soon as possible, reduce storage pressure and reduce potential loss risks. Specifically, the scheduling plan may include measures such as increasing the scheduling frequency of transport vehicles and optimizing the loading and unloading operation process. For example, in one embodiment, the system generates a new scheduling plan to ship the above-mentioned high-cost goods in advance to reduce further delays and losses caused by bad weather.

[0067] Through the above steps, the present invention can effectively respond to severe weather information based on forecasts, reasonably adjust the priority ranking of goods, and improve the operational efficiency and risk resistance of the port supply chain.

[0068] Next, refer to Figure 8 , describing the steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information in the seventh embodiment of the present invention.

[0069] S801: Obtain the transportation distance D_transport of each cargo; S802: Calculate the transportation cost T_cost = C1 × D_transport + C2, where C1 is the fixed transportation cost per kilometer and C2 is the additional transportation fixed cost; S803: If the predicted bad weather duration D > T10, T10 is a preset threshold, and the transportation cost T_cost > T11, T11 is a preset threshold, the goods with high transportation cost are processed first; S804: Update the dispatch plan and optimize the transportation cost.

[0070] Get the transport distance D_transport of each cargo, which refers to the straight-line or actual route distance from the port to the destination, usually in kilometers. This step is used to understand the distance of each cargo, so as to assess the difficulty and possible risks of transportation. For example, for a cargo departing from Shanghai Port, if the destination is Melbourne, Australia, then the D_transport of the cargo is about 7462 kilometers; if the destination is Guangzhou, China, then the D_transport of the cargo may be only about 800 kilometers.

[0071] Subsequently, the transportation cost of each cargo is calculated as T_cost = C1 × D_transport + C2, where C1 is the fixed transportation cost per kilometer, which usually varies between RMB 1 and RMB 5, depending on the mode of transportation and service quality; C2 is the additional fixed transportation cost, which usually fluctuates between RMB 100 and RMB 1,000, covering loading, unloading and other management costs. The purpose of this formula is to quantify the cost difference of transportation under different distances and conditions. By setting reasonable C1 and C2, ensure that the calculated cost can truly reflect the actual logistics situation. For example, in a specific embodiment, for cargo with a transportation distance of 7462 kilometers, if C1=3 yuan / kilometer and C2=500 yuan are set, then T_cost = 3 × 7462 + 500 = 22886 yuan.

[0072] Next, determine whether specific conditions under severe weather conditions are met: the predicted duration of severe weather D > T10 (such as 5 hours), T10 is the preset threshold; at the same time, the transportation cost T_cost > T11 (such as 20,000 yuan), T11 is also the preset threshold. Setting T10 to 5 hours here means that the priority of the goods will be adjusted only when the severe weather is expected to last longer than this time, and T11 is used as a cost threshold to screen out those goods that will not increase the cost much even if delayed. Such a design ensures the rational allocation of resources and avoids over-response. Specifically, if the severe weather is expected to last for 6 hours and the transportation cost of a high-value electronic product is 23,000 yuan, the product will be given priority if D > T10 and T_cost > T11 are met.

[0073] Finally, update the scheduling plan to optimize transportation costs. Once it is confirmed that the priority needs to be adjusted, the system will rearrange the order of loading and unloading, try to give priority to the goods that are more affected and have higher costs, and ensure that key transportation tasks are completed before the bad weather arrives. For example, if a batch of high-cost goods is about to be loaded, and bad weather is about to affect the transportation of this route, the transportation of these goods will be arranged in advance to ensure that the overall efficiency and cost control of the supply chain are not seriously affected.

[0074] Through the above steps, this method can quickly and efficiently adjust the processing order of goods when facing uncertain severe weather, minimize losses and delays, and enhance the risk resistance of port operations.

[0075] Next, refer to Fig. 9 , describing the steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information in an eighth embodiment of the present invention.

[0076] S901: Obtain the importance of each cargo I_importance; S902: Calculate the importance factor A_factor = I_importance / T12, where T12 is a preset importance threshold; S903: If the predicted severe weather impact range W_influence covers the critical transportation path and the importance impact factor A_factor > T13, where T13 is a preset threshold, the priority of the important goods is increased; S904: Update the dispatch plan to ensure the timely delivery of important goods.

[0077] First, the importance of each cargo I_importance is obtained from the port supply chain platform. Here, the importance I_importance reflects the value of the cargo in the supply chain and can be divided into multiple levels from high to low, for example, level 1, level 2, and level 3. Specifically, this may include high-value goods, emergency relief supplies, or items with strict time requirements.

[0078] Then, the importance factor A_factor is calculated based on the obtained importance. The calculation formula is A_factor = I_importance / T12, where T12 is the preset importance threshold. This threshold T12 is determined based on historical data and experience, and is generally set to the average importance of medium-importance goods. By applying this formula, it is ensured that high-importance goods can get higher priority even in bad weather conditions. For example, if T12 is set to 70 points, and the importance of a batch of goods I_importance is 85 points, then the calculated A_factor is 1.21.

[0079] Then, if the bad weather influence range W_influence obtained from the weather forecast covers the key transportation path of the goods, and the importance influence factor A_factor exceeds the preset threshold T13, T13 is usually a decimal less than 1 but greater than 0.5, which is used to determine whether the goods really need to be transported in bad weather. For example, T13 is set to 1.0, which means that the priority of the goods will be increased only when A_factor is greater than 1. This setting can effectively avoid the waste of resources caused by excessively increasing the priority of goods.

[0080] Finally, once the conditions are met, the system will update the scheduling plan and rearrange the order of cargo flow to ensure that truly important and urgently needed cargo can be processed and delivered in a timely manner under severe weather conditions. For example, in one embodiment, if a typhoon is predicted to affect a port tomorrow, causing some routes to be suspended, the system detects that a batch of high-value electronic components has an I_importance of 90 points, and the calculated A_factor is 1.29, which is significantly higher than T13 (set to 1.0). Therefore, this batch of goods will be given priority to leave the port on the last liner before the weather changes to reduce potential losses and meet customer needs.

[0081] Next, refer to Fig.10 , describing the steps of adjusting the priority sorting of cargo in a port based on predicted severe weather information in a ninth embodiment of the present invention.

[0082] S1001: Get the urgency of each cargo E_urgency; S1002: Calculate the urgency weight E_weight = E_urgency / W_warehouse, where W_warehouse is the maximum capacity of the warehouse; S1003: If the predicted severe weather intensity G > T14, T14 is a preset threshold, and the urgency weight E_weight > T15, T15 is a preset threshold, the goods with high urgency are processed first; S1004: Update dispatch plans to reduce cargo delays.

[0083] First, obtain the urgency of each shipment. The urgency here refers to the importance of the shipment arriving at the destination within the scheduled time. This value is usually provided by the owner of the shipment or the supply chain management system and ranges from 0 to 100, where 0 is the least urgent and 100 is the most urgent. For example, medical supplies or critical manufacturing parts may have a high urgency value.

[0084] Then, the urgency weight E_weight = E_urgency / W_warehouse is calculated, where W_warehouse is the maximum capacity of the warehouse. The maximum capacity W_warehouse is usually known and is used to normalize the urgency to ensure that the calculated weight is within a reasonable range. The purpose of this formula is to combine the urgency of the goods with their proportion in the port warehouse, so that large goods with high urgency will not affect their priority due to their quantity. For example, if the maximum capacity of a port warehouse is 1000 units, and a cargo with an urgency of 80 occupies 500 units, its urgency weight E_weight = 80 / 1000 = 0.08.

[0085] Next, check whether the predicted severe weather intensity G is greater than the preset threshold value T14, and check whether the urgency weight E_weight is greater than another preset threshold value T15. These two thresholds are used to determine whether the goods need to be given priority. T14 can range from 1 to 10, where 1 represents mild bad weather and 10 represents extremely bad weather. The optimal value is usually set to 6 or 7, indicating more severe bad weather. T15 can range from 0.01 to 0.5, indicating the importance of the urgency of the goods. The optimal value is usually set to 0.08, indicating that goods with a higher degree of urgency need to be given priority. If both conditions are met, goods with a higher degree of urgency are given priority. The purpose of this condition setting is to ensure that the most important goods can be handled in a timely manner in extremely severe weather conditions to avoid greater losses.

[0086] Finally, update the scheduling plan to reduce cargo delays. Specifically, this step involves adjusting the order of cargo flow and reallocating human and equipment resources to speed up the processing of urgent cargo. In one embodiment, assume that the port weather station predicts that a strong typhoon will hit, and the predicted severe weather intensity G = 8, far exceeding the preset threshold T14 = 6. At the same time, a batch of medical epidemic prevention materials E_urgency = 90, occupying 100 units in the warehouse, and calculated E_weight = 90 / 1000 = 0.09 > T15 = 0.08. Therefore, the system decides to prioritize the dispatch of this batch of medical epidemic prevention materials to ensure that they can arrive at the destination in the shortest time, thereby reducing potential delays and risks.

[0087] A control method based on a port supply chain platform of the present invention includes: obtaining real-time meteorological data of the port and predicting the impact range and duration of bad weather based on these data, so as to grasp in advance the possible meteorological changes and their specific impact on port operations. Then, the method dynamically adjusts the priority sorting of goods in the port based on the predicted bad weather information. This priority sorting is based on the importance of the goods, the delivery deadline, and the risk of being affected by bad weather, so as to ensure that high-value or time-sensitive goods can be loaded and unloaded and transported first before the bad weather, thereby minimizing losses and delays.

[0088] In addition, the control method dynamically updates the cargo dispatch plan through the port supply chain platform. This means that once bad weather or other emergencies are predicted, port managers can adjust the order and route of cargo loading and unloading in a timely manner through the platform to reduce cargo delays caused by weather. At the same time, the platform can also provide real-time feedback to help decision makers better monitor and control the entire logistics process.

[0089] In order to solve the inventory management and scheduling conflicts that occur during severe weather, the present invention further optimizes the port inventory management strategy. Specifically, through reasonable warehousing arrangements and rapid response mechanisms, the effective utilization of warehouses can be guaranteed even during severe weather, cargo accumulation can be avoided, and warehouse pressure can be reduced. For example, when a strong typhoon is predicted, vulnerable goods can be transferred to a safer location in advance, or the delivery speed of certain goods can be accelerated, thereby ensuring maximum utilization of warehouse internal resources. This series of measures together constitute a complete solution that effectively solves the inventory management and scheduling conflicts caused by cargo detention and delays under the influence of severe weather.

[0090] In addition, if Fig.11 As shown, the present application also provides a control system 1100 based on a port supply chain platform, which includes: The data acquisition module 1101 acquires the real-time weather data of the port and predicts the impact range and duration of the bad weather according to the weather data; A prioritization module 1102 adjusts the priority of cargo in the port based on the predicted severe weather information; The scheduling module 1103 dynamically updates the cargo scheduling plan through the port supply chain platform to reduce cargo detention and delays; The strategy issuance module 1104 optimizes the port inventory management strategy to ensure the rational utilization and rapid response of warehouses during severe weather.

[0091] The functions of the various components of the control system 1100 based on the port supply chain platform of the present application have been described above with reference to the accompanying drawings and will not be repeated here.

[0092] The above is a preferred embodiment of the present application. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A control method based on a port supply chain platform, characterized in that: include: Obtaining real-time weather data of the port and predicting the impact range and duration of severe weather based on the weather data; Adjust the priority sorting of cargo within the port based on predicted severe weather information; Dynamically update cargo dispatch plans through the port supply chain platform to reduce cargo detention and delays; Optimize port inventory management strategies to ensure rational utilization and rapid response of warehouses during severe weather.

2. A control method based on a port supply chain platform according to claim 1, characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information includes: Get real-time weather data and forecast severe weather intensity level G; Cargo in the port is divided into three categories according to the predicted intensity level G: high priority, medium priority and low priority; If the predicted intensity level G > T1, the susceptible goods are classified as high priority, and other goods are classified as medium priority and low priority in sequence; Dynamically adjust cargo dispatch plans and give priority to high-priority cargo to reduce cargo detention and delays.

3. A control method based on a port supply chain platform according to claim 2, characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Collect basic information of each shipment, including weight W, volume V and value P; Calculate the risk index R of each cargo, risk index R = (W + V + P) / 3; If the predicted duration of bad weather D > T2, where T2 is a preset threshold, the priority of cargo with a risk index R above a certain threshold R > T3 is increased, where T3 is a preset threshold; Update dispatch plans to prioritize cargo with high risk indices.

4. The control method based on the port supply chain platform according to claim 3 is characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Get the loading and unloading time Ti and transportation time Ti of each cargo; Calculate the total time for the goods Ti_total = Ti + Ti; If the predicted bad weather duration D > T2 and the total time Ti_total > T4, where T4 is the preset threshold, the priority of the cargo is increased; Update the dispatch plan to give priority to shipments with the longest total processing time.

5. A control method based on a port supply chain platform according to claim 4, characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Get the information of the destination city Ci of the goods; Calculate the average distance D_average from the destination city Ci to the current port; If the predicted bad weather impact range W_influence covers the target city Ci and the average distance D_average > T5, where T5 is the preset threshold, the priority of the cargo is increased; Update dispatch plans to prioritize shipments that are transported over long distances.

6. A control method based on a port supply chain platform according to claim 5, characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Get the value fluctuation coefficient V_fluc of each commodity; Calculate the value change rate of each cargo C_rate = (V_end-V_start) / V_start, where V_end and V_start are the estimated value after reaching the destination and the current value respectively; If the predicted severe weather intensity G > T6, T6 is the preset threshold, and the value change rate C_rate < T7, T7 is the preset threshold, then the priority of the cargo is lowered; Update dispatch plans to prioritize shipments with high value fluctuations.

7. A control method based on a port supply chain platform according to claim 6, characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Get the storage time T_store of each product; Calculate the storage cost F_cost = K×T_store, where K is the storage cost per unit time; If the predicted duration of bad weather D > T8, T8 is the preset threshold, and the storage cost F_cost > T9, T9 is the preset threshold, the goods with longer storage time will be processed first; Update scheduling plans to reduce warehouse storage pressure.

8. The control method based on the port supply chain platform according to claim 7 is characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Get the transportation distance D_transport of each cargo; Calculate the transport cost T_cost = C1 × D_transport + C2, where C1 is the fixed transport cost per kilometer and C2 is the additional fixed cost of transport; If the predicted bad weather duration D > T10, T10 is the preset threshold, and the transportation cost T_cost > T11, T11 is the preset threshold, the goods with high transportation cost are processed first; Update dispatch plans to optimize transportation costs.

9. A control method based on a port supply chain platform according to claim 8, characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Get the importance of each cargo I_importance; Calculate the importance factor A_factor = I_importance / T12, where T12 is the preset importance threshold; If the predicted severe weather impact range W_influence covers the critical transportation path and the importance impact factor A_factor > T13, where T13 is the preset threshold, the priority of important goods will be increased; Update dispatch plans to ensure timely delivery of important shipments.

10. A control method based on a port supply chain platform according to claim 9, characterized in that: The adjustment of the priority sorting of cargo in the port based on the predicted severe weather information also includes: Get the urgency of each cargo E_urgency; Calculate the urgency weight E_weight = E_urgency / W_warehouse, where W_warehouse is the maximum capacity of the warehouse; If the predicted severe weather intensity G > T14, T14 is the preset threshold, and the urgency weight E_weight > T15, T15 is the preset threshold, the cargo with high urgency will be processed first; Update dispatch plans to reduce cargo delays.

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