Intelligent management and control method, system and equipment for port and waterway logistics

Abstract

The invention provides an intelligent management and control method, system and equipment for port and waterway logistics, and belongs to the technical field of port and waterway logistics. The method comprises the following steps: acquiring port and navigation logistics information from a cloud; determining a transportation route network and a cargo transportation time period set based on the port and aviation logistics information and a preset logistics transportation distribution model; according to the transportation route network, the cargo transportation time period set and a preset DP algorithm, the cargos to be conveyed are distributed to one or more corresponding first distribution cargo ships, and initial arrival time nodes of the first distribution cargo ships at the staying ports are determined; based on each initial arrival time node, determining each corresponding port evaluation score, and comparing each port evaluation score with a preset management and control evaluation threshold; and updating the initial arrival time node according to a comparison result of each port evaluation score and a preset management and control evaluation threshold and a preset correction rule so as to adjust the transportation plan and the loading and unloading plan.

Description

Technical Field

[0001] The present application relates to the field of port and shipping logistics technology, and in particular to a method, system and equipment for intelligent management and control of port and shipping logistics. Background Art

[0002] In the modern port and shipping logistics system, with the continuous growth of global trade, the volume of cargo transactions that rely on inland waterway transportation has increased significantly. However, the traditional port and shipping logistics management methods have many shortcomings, such as unreasonable transportation route planning, unclear cargo transportation time limit, chaotic port berth allocation, logistics transportation traffic congestion and other issues, which seriously restrict the efficiency and benefits of port and shipping logistics.

[0003] Traditional port and shipping logistics information management mainly relies on manual experience and lacks intelligent decision-making support. The choice of transportation routes is often based on experience and judgment, and it is difficult to comprehensively consider the impact of various factors (such as waterway conditions, traffic flow, weather conditions, etc.) on transportation efficiency. At the same time, the setting of cargo transportation time limits also lacks scientific basis, resulting in cargo being in transit for too long or too short a time, increasing transportation costs and risks.

[0004] In addition, the allocation of port berths and the management of logistics and transportation traffic also face many challenges. Due to the limited berth resources and the large number of cargo ships, berth allocation often leads to conflicts and confusion. At the same time, the congestion of logistics and transportation traffic has also seriously affected the loading and unloading efficiency and transportation speed of goods, bringing a bad logistics experience to users. Summary of the invention

[0005] The embodiments of the present application provide a method, system and equipment for intelligent management and control of port and shipping logistics, which are used to solve the technical problems that the current port and shipping logistics management and control relies too much on manual experience and has a low level of intelligence, which may bring a series of problems to port and shipping logistics transportation, berth management, and transportation, and affect the user experience of port and shipping logistics.

[0006] On the one hand, an embodiment of the present application provides a method for intelligent management and control of port and shipping logistics, the method comprising:

[0007] Obtaining port and shipping logistics information from the cloud; wherein the port and shipping logistics information at least includes cargo transaction information, waterway conditions, traffic flow, and weather conditions that rely on inland waterway transportation;

[0008] Based on the port and shipping logistics information and the preset logistics transportation allocation model, determine the transportation route network and the cargo transportation time period set;

[0009] According to the transport route network, the cargo transport time period set and the preset DP algorithm, each cargo to be transported is respectively allocated to one or more corresponding first allocated cargo ships, and the initial arrival time node of the first allocated cargo ship at each stop port is determined;

[0010] Based on each of the initial arrival time nodes, determine the corresponding port assessment score to compare each of the port assessment scores with a preset control assessment threshold; wherein the port assessment score is obtained based at least on the berth urgency, logistics and transportation traffic conditions, and arrival time node matching degree corresponding to the initial arrival time node;

[0011] According to the comparison results of the assessment scores of each port with the preset control assessment threshold and the preset correction rules, the initial arrival time node is updated to adjust the transportation plan and loading and unloading plan.

[0012] In one implementation of the present application, based on the port and shipping logistics information and the preset logistics transportation allocation model, a transportation route network and a set of cargo transportation time periods are determined, specifically including:

[0013] The port and shipping logistics information is used as a model input parameter and input into the preset logistics transportation allocation model to determine the transportation route network according to the model output result; wherein the preset logistics transportation allocation model is a pre-trained multi-objective optimization model; the multi-objective optimization model includes a comprehensive objective function with at least transportation cost and transportation time as objective functions;

[0014] According to the transportation route network, the preset transportation time period division standard, and the cargo transaction information, the corresponding goods to be transported are clustered to obtain sets of cargo transportation time periods corresponding to different cargo attribute sets; wherein, one cargo transportation time period set includes one or more goods to be transported corresponding to the same cargo attribute set and one or more transportation time periods corresponding thereto; the cargo attribute set is obtained based on clustering the cluster feature vectors corresponding to the transportation route network, the preset transportation time period division standard, and the cargo transaction information.

[0015] In one implementation of the present application, according to the transportation route network, the cargo transportation time period set, and the preset DP algorithm, each cargo to be transported is respectively allocated to one or more corresponding first allocated cargo ships, and the initial arrival time node of the first allocated cargo ship at each stop port is determined, specifically including:

[0016] According to the transportation route network, the cargo transportation time period set, and the preset DP algorithm, traverse each achievable transportation route and each achievable transportation time period corresponding to the cargo to be transported, and generate each achievable transportation tuple;

[0017] Matching each of the achievable transport tuples with a preset port cargo ship berthing list to generate a sequence of transport cargo ships to be allocated according to the matching results; wherein the preset port cargo ship berthing list includes a number of transport cargo ship labels to be allocated, routes and port planned berthing times;

[0018] Based on the cargo ship full load rate, cargo transportation attributes and preset allocation conditions, in the order of the sequence of cargo ships to be allocated, it is judged in turn whether the cargo to be transported can be allocated to the current cargo ship; wherein the cargo ship full load rate includes volume full load rate and weight full load rate; the cargo transportation attributes include at least cargo volume and cargo weight; the preset allocation conditions include at least that the cargo transportation attributes are in the remaining loadable capacity interval; the remaining loadable capacity interval is obtained based on the cargo ship full load rate and the maximum load capacity of the cargo ship, and includes a remaining volume loading rate sub-interval and a remaining weight loading sub-interval;

[0019] If yes, update the cargo ship full load rate of the current cargo ship according to the cargo transportation attribute, and use the current cargo ship as the first allocated cargo ship; otherwise, determine whether the cargo to be transported can be allocated to the next cargo ship until the first allocated cargo ship is determined;

[0020] According to the historical sailing record of the first allocated cargo ship, the corresponding initial arrival time nodes are determined.

[0021] In one implementation of the present application, the method further includes:

[0022] In the case that there is no first allocated cargo ship that can allocate the cargo to be transported, determining whether the cargo to be transported is cargo that can be transported in batches;

[0023] If so, the cargo to be transported is divided into multiple batches of cargo units to be transported according to the preset minimum batch specification corresponding to the cargo to be transported, and each of the cargo units to be transported is judged in turn whether it can be allocated to the current cargo ship, until all the cargo units to be transported are allocated to multiple cargo ships in the sequence of cargo ships to be allocated, so that the cargo ship to which the cargo units to be transported are allocated is used as the first allocated cargo ship;

[0024] Otherwise, a manual intervention prompt message is generated and sent to the user terminal so that the first allocated cargo ship for the cargo to be transported is manually designated.

[0025] In one implementation of the present application, based on each of the initial arrival time nodes, the corresponding port evaluation scores are determined, specifically including:

[0026] According to the initial arrival time node, determining the corresponding berth occupancy rate and the number of ships waiting for berths, so as to calculate the berth urgency of the stop port at the initial arrival time node;

[0027] Matching the initial arrival time node with a preset traffic condition list to determine the road congestion index, average transportation time, and average transportation cost of the city network corresponding to the stopover port to calculate the logistics transportation traffic condition;

[0028] Calculating the time difference between the initial arrival time node and the preset port operation time, and determining the matching degree of the arrival time node according to the time difference, the preset time difference threshold, and the maximum allowable time difference value;

[0029] The weighted product value of the berth urgency, the logistics transportation traffic conditions and the arrival time node matching degree is used as the port evaluation score of the corresponding stopover port at the initial arrival time node.

[0030] In one implementation of the present application, the initial arrival time node is matched with a preset traffic condition list to determine the road congestion index, average transportation time, and average transportation cost of the city network corresponding to the stopover port, specifically including:

[0031] Determine the corresponding types of transport vehicles according to the cargo transport attributes of the cargo loaded and unloaded at the stop port;

[0032] The road congestion index, the average transportation time, and the average transportation cost are determined according to the transport vehicle type and the preset traffic impact list corresponding to the urban network; wherein the preset traffic impact list includes the road congestion index, the average transportation time, and the average transportation cost of different transport vehicle types arriving at different locations at different times.

[0033] In one implementation of the present application, determining the arrival time node matching degree according to the time difference and a preset time difference threshold and a maximum allowable time difference value specifically includes:

[0034] When the time difference is less than or equal to the preset time difference threshold, determining that the arrival time node matching degree is 1;

[0035] When the time difference is greater than the preset time difference threshold and less than or equal to the maximum allowable time difference value, the arrival time node matching degree is determined to be Among them, T th is the preset time difference threshold, ΔT is the time difference, and δ is the maximum allowable value of the time difference;

[0036] When the time difference is greater than the maximum allowed value of the time difference, it is determined that the arrival time node matching degree is 0.

[0037] In one implementation of the present application, the initial arrival time node is updated according to the comparison result of each port evaluation score with the preset control evaluation threshold and the preset correction rule, specifically including:

[0038] When the port evaluation score is less than the preset control evaluation threshold, determining a controllable time interval for the first allocated cargo ship to arrive at the stop port; wherein the controllable time interval at least includes the initial arrival time node;

[0039] According to the controllable time interval, generating a port evaluation score curve corresponding to each controllable arrival time node;

[0040] Determine the time nodes in the port assessment score curve that are greater than or equal to the preset control assessment threshold, and add the time nodes to the sequence of arrival time nodes to be selected in order of the difference between the time nodes and the initial arrival time nodes from small to large;

[0041] The sequence of arrival time nodes to be selected is sent to the user terminal, so that based on the user's operation of selecting the time node, the selected arrival time node to be selected is updated to the initial arrival time node, so as to adjust the transportation plan and the loading and unloading plan according to the updated initial arrival time node.

[0042] On the other hand, the embodiment of the present application also provides an intelligent management and control system for port and shipping logistics, the system comprising:

[0043] An acquisition module, used to acquire port and shipping logistics information from the cloud; wherein the port and shipping logistics information at least includes cargo transaction information, waterway conditions, traffic flow, and weather conditions that rely on inland waterway transportation;

[0044] A first determination module is used to determine a transportation route network and a set of cargo transportation time periods based on the port and shipping logistics information and a preset logistics transportation allocation model;

[0045] An allocation module is used to allocate each cargo to be transported to one or more corresponding first allocation cargo ships according to the transportation route network, the cargo transportation time period set, and a preset DP algorithm, and determine the initial arrival time node of the first allocation cargo ship at each stopover port;

[0046] A second determination module is used to determine the corresponding port evaluation score based on each of the initial arrival time nodes, so as to compare the port evaluation score with a preset control evaluation threshold; wherein the port evaluation score is obtained based at least on the berth urgency, logistics and transportation traffic conditions, and arrival time node matching degree corresponding to the initial arrival time node;

[0047] The updating module is used to update the initial arrival time node according to the comparison result of each port evaluation score with the preset control evaluation threshold and the preset correction rule to adjust the transportation plan and the loading and unloading plan.

[0048] On the other hand, the embodiment of the present application further provides a port and shipping logistics intelligent management and control device, the device comprising:

[0049] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method for intelligent management and control of port and shipping logistics as described above.

[0050] Compared with the prior art, the present invention has the following significant effects:

[0051] Through the above scheme, this application can generate a transportation route network and a collection of cargo transportation time periods in combination with port logistics information, realize transportation route planning and provide clear time limits, and flexibly allocate cargo ships for cargo. Under the comprehensive multi-dimensional factors, the initial arrival time node set for the cargo ship is dynamically evaluated to adjust the initial arrival time node to optimize the transportation plan and improve loading and unloading efficiency and transportation speed. It solves the problem that port and shipping logistics management is too dependent on manual experience, the level of intelligence is not high, and a series of problems brought to port and shipping logistics transportation, berth management, and transportation, and improves the user experience of port and shipping logistics. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0053] Figure 1 A schematic diagram of a process of an intelligent management and control method for port and shipping logistics in an embodiment of the present application;

[0054] Figure 2 This is a structural diagram of an intelligent management and control system for port and shipping logistics in an embodiment of the present application;

[0055] Figure 3 This is a structural schematic diagram of an intelligent management and control device for port and shipping logistics in an embodiment of the present application. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0057] The embodiments of the present application provide a method, system and equipment for intelligent management and control of port and shipping logistics, which are used to solve the technical problems that the current port and shipping logistics management and control relies too much on manual experience and has a low level of intelligence, which may bring a series of problems to port and shipping logistics transportation, berth management, and transportation, and affect the user experience of port and shipping logistics.

[0058] The following describes in detail various embodiments of the present application in conjunction with the accompanying drawings.

[0059] The present application embodiment provides a method for intelligent management and control of port and shipping logistics, such as Figure 1 As shown, the method may include steps S101-S105:

[0060] S101, the server obtains port and shipping logistics information from the cloud.

[0061] Among them, port and shipping logistics information at least includes cargo trading information, waterway conditions, traffic flow, and weather conditions that rely on inland waterway transportation.

[0062] It should be noted that the server, as the executor of the intelligent management and control method for port and shipping logistics, is only an example. The executor is not limited to the server, and this application does not make any specific limitations on this.

[0063] The server can be connected to the cloud server through the network, and the cloud can collect data uploaded by users using the port and shipping logistics platform, including but not limited to cargo transaction information, waterway conditions, traffic flow, and weather conditions. Among them, cargo transaction information can be cargo orders and delivery related information submitted by users, which can specifically cover the information of both parties to the transaction, the cargo information of the transaction, the time and place of the transaction; waterway conditions can include waterway depth, waterway width, waterway turning radius, waterway permitted flow rate, and water contour, which can come from the user terminal corresponding to the waterway management department; traffic flow is the number of vehicles passing through a specified section of the road per unit time, which can come from the traffic management department; weather conditions include but are not limited to temperature, humidity, and wind force, which can come from the meteorological bureau.

[0064] The server can obtain real-time port and shipping logistics information related to port and shipping logistics through the cloud.

[0065] S102, the server determines the transportation route network and the cargo transportation time period set based on the port and shipping logistics information and the preset logistics transportation allocation model.

[0066] In the embodiment of the present application, based on the port and shipping logistics information and the preset logistics transportation allocation model, the transportation route network and the cargo transportation time period set are determined, specifically including:

[0067] The port and shipping logistics information is used as a model input parameter and input into a preset logistics transportation allocation model to determine the transportation route network according to the model output result. The preset logistics transportation allocation model is a pre-trained multi-objective optimization model. The multi-objective optimization model includes a comprehensive objective function with at least transportation cost and transportation time as objective functions. According to the transportation route network, the preset transportation time division standard, and the cargo transaction information, the corresponding goods to be transported are clustered to obtain sets of cargo transportation time periods corresponding to different cargo attribute sets. A cargo transportation time period set includes one or more goods to be transported corresponding to the same cargo attribute set and one or more corresponding transportation time periods. The cargo attribute set is obtained based on clustering the cluster feature vectors corresponding to the transportation route network, the preset transportation time division standard, and the cargo transaction information.

[0068] In other words, the present application adopts transportation cost and transportation time as objective functions to construct a comprehensive objective function. The comprehensive objective function can be obtained by weighted summing the transportation cost objective function and the transportation time objective function through the first weight and the second weight respectively. The first weight and the second weight can be set according to the actual usage scenario, and the present application does not make specific restrictions on this. The comprehensive objective function is such as:

[0069]

[0070] Among them, F(x) is the comprehensive objective function corresponding to the x-th port and shipping logistics information, w i is the weight of the i-th objective function, in this embodiment n=2, f i (x) The i-th objective function corresponding to the x-th port and shipping logistics information.

[0071] The comprehensive objective function serves as the objective function of the multi-objective optimization model. The multi-objective optimization model can be the NSGA-II algorithm or the MOEA / D algorithm, which is not specifically limited in this application. Before processing the port and shipping logistics information through the multi-objective optimization model, this application will also perform data preprocessing, including data cleaning, denoising, missing value processing, and normalization processing, and then perform optimization processing. When the function value of the comprehensive objective function is less than the predetermined value, a transportation route network corresponding to the port and shipping logistics information is obtained. The transportation route network can be understood as the river transportation route network involved in the port and shipping logistics information corresponding to a port. The transportation route network includes routes triggered from the port to other ports.

[0072] Furthermore, the server will cluster goods according to the goods transaction information, transportation route network, and preset transportation time division standards. The preset transportation time division standards are pre-established standards, such as the urgency of the goods (such as whether they need to be delivered as soon as possible), transportation costs (such as fuel costs and port fees at different times), traffic flow (such as waterway congestion at different times), and weather conditions (such as the impact of temperature and humidity on goods at different times). Different standards correspond to different transportation time periods. For example, transportation time periods are divided into peak hours (such as daytime and weekends, when waterways are congested and costs are high), off-peak hours (such as weekday evenings and early mornings, when waterways are relatively unobstructed and costs are low), and special hours (such as extreme weather conditions, which require special arrangements for transportation time and methods).

[0073] Specifically, the present application can select features that have an important impact on clustering from cargo transaction information, such as cargo type, destination, delivery time requirements, etc., through clustering algorithms such as K-means, and convert the transportation route network and the preset transportation time division standard into features that have an impact on clustering, such as the transportation distance of the cargo, whether the expected transportation time matches a specific time period, etc., and then construct a clustering feature vector, and perform clustering processing on the clustering feature vectors of each cargo to be transported, so as to divide each cargo to be transported into different cluster clusters, that is, cargo attribute sets. According to the delivery time requirements of the cargo to be transported and the preset transportation time division standard, the cargo transportation time period set corresponding to each cargo attribute set is obtained, so that each cargo attribute set is associated with its corresponding cargo transportation time period set. Each cargo attribute set consists of one or more similar cargo to be transported, and they correspond to the same one or more transportation time periods. For example, a batch of cargo to be transported is processed as above, and three cargo attribute sets A, B, and C can be obtained. A contains two types of cargo to be transported, a1 and a2. Through the preset transportation time division standard, it can be further obtained that A corresponds to the peak time period, then the cargo transportation time period set is {a1 = peak time period, a2 = peak time period}. In addition, if the clustering result is not ideal, you can adjust the parameters of the clustering algorithm, such as the K value in K-means, re-execute the clustering algorithm, and verify the new clustering result until the clustering result is ideal.

[0074] Through the above scheme, the transportation route network and the cargo transportation time period set can be accurately and efficiently obtained. According to the transportation route network, the preset transportation time period division standard and the cargo transaction information, the cargo attribute set is clustered, and the cargo transportation time period set corresponding to different cargo attribute sets is generated. This helps to formulate a more reasonable and efficient transportation plan and improve the efficiency of logistics transportation and customer satisfaction.

[0075] S103, the server allocates each cargo to be transported to one or more corresponding first allocated cargo ships according to the transportation route network, cargo transportation time period set and preset DP algorithm, and determines the initial arrival time node of the first allocated cargo ship at each stopover port.

[0076] In the embodiment of the present application, according to the transportation route network and the cargo transportation time period set and the preset DP algorithm, each cargo to be transported is respectively allocated to one or more corresponding first allocation cargo ships, and the initial arrival time node of the first allocation cargo ship at each stopover port is determined, specifically including:

[0077] According to the transport route network and the set of cargo transport time periods and the preset DP algorithm, each achievable transport route and each achievable transport time period corresponding to the cargo to be transported are traversed to generate each achievable transport tuple. Each achievable transport tuple is matched with the preset port cargo ship berthing list to generate a sequence of cargo ships to be allocated for transport according to the matching result. Among them, the preset port cargo ship berthing list includes several labels of cargo ships to be allocated for transport, routes and planned port berthing times. Based on the cargo ship full load rate, cargo transportation attributes and preset allocation conditions, according to the order of the sequence of cargo ships to be allocated for transport, it is judged in sequence whether the cargo to be transported can be allocated to the current cargo ship. Among them, the cargo ship full load rate includes volume full load rate and weight full load rate. The cargo transportation attributes include at least cargo volume and cargo weight. The preset allocation conditions include at least that the cargo transportation attributes are in the remaining loadable capacity interval. The remaining loadable capacity interval is obtained based on the cargo ship full load rate and the maximum load capacity of the cargo ship, including the remaining volume loading rate sub-interval and the remaining weight loading sub-interval. If it is determined that the cargo to be transported can be allocated to the current cargo ship, the cargo ship full load rate of the current cargo ship is updated according to the cargo transportation attributes, and the current cargo ship is used as the first allocated cargo ship. Otherwise, it is determined whether the cargo to be transported can be allocated to the next cargo ship until the first allocated cargo ship is determined. According to the historical navigation records of the first allocated cargo ship, the corresponding initial arrival time nodes are determined.

[0078] That is to say, after obtaining the above-mentioned transport route network and cargo transport time period set, the present application will further allocate cargo ships for the cargo to be transported, and estimate the initial arrival time node of the first allocated cargo ship to arrive at the stop port.

[0079] Specifically, the present application uses a preset dynamic programming (DP) algorithm, which can pre-set an array to store the distribution of each cargo in the port and transportation period, and set a variable to record the full load rate of the current cargo ship. Traverse each possible transportation route and transportation period of the cargo to be transported, so as to construct multiple reachable transportation tuples, such as the reachable transportation tuple of the cargo M to be transported is [transportation route L1, transportation period t1], [transportation route L2, transportation period t2]... Then, each reachable transportation tuple is matched with the preset port cargo ship berthing list to obtain the to-be-allocated transportation cargo ship corresponding to the reachable transportation tuple, and generate a sequence of to-be-allocated transportation cargo ships in the order of the reachable transportation tuples. The reachable transportation tuple includes a reachable transportation route that can transport the cargo to be transported and a reachable transportation period within the required transportation time limit.

[0080] Subsequently, the server will traverse the to-be-allocated transport cargo ships in the order of the to-be-allocated transport cargo ship sequence, and judge in turn whether the to-be-transported cargo can be allocated to the current cargo ship. The judgment basis can be calculated by the cargo ship full load rate of the current cargo ship and its maximum cargo ship load capacity, and the remaining loadable capacity interval of the cargo ship can be calculated. If the cargo transportation attribute of the to-be-transported cargo is within the remaining loadable capacity interval, the preset allocation condition is met, and the to-be-transported cargo can be allocated to the current cargo ship. At this time, the server will update the cargo ship full load rate of the current cargo ship, and the cargo ship full load rate includes two dimensions, the loading volume dimension and the state weight dimension. At the same time, the current cargo ship is used as the first allocated cargo ship. If the preset allocation condition is not met, the server will continue to traverse along the to-be-allocated transport cargo ship sequence until the first allocated cargo ship is obtained. After the server obtains the first allocated cargo ship, it can search its historical navigation record according to its cargo ship label. The historical navigation record includes its average navigation speed and arrival time data. By analyzing the historical navigation record, the initial arrival time node of the first allocated cargo ship arriving at each stopover port can be obtained. The analysis process can be achieved by pre-training a machine learning model, and this application does not make specific limitations on this.

[0081] In addition, in one embodiment of the present application, when there is no first allocated cargo ship to be allocated to the cargo to be transported, it is determined whether the cargo to be transported is cargo that can be transported in batches. When it is determined that the cargo to be transported is cargo that can be transported in batches, the cargo to be transported is divided into multiple batches of cargo units to be transported according to the preset minimum batch specifications corresponding to the cargo to be transported, and it is judged in turn whether each cargo unit to be transported can be allocated to the current cargo ship, until all cargo units to be transported are allocated to multiple cargo ships in the sequence of cargo ships to be allocated, so that the cargo ship to which the cargo unit to be transported is allocated is used as the first allocated cargo ship. When it is determined that the cargo to be transported is not cargo that can be transported in batches, a manual intervention prompt message is generated and sent to the user terminal, so that the first allocated cargo ship to be transported is manually specified.

[0082] In other words, the goods to be transported may not be allocated to the same cargo ship. At this time, the server will check whether the goods to be transported carry a batchable label to determine whether the goods to be transported are goods that can be transported in batches. If the transportation can be allocated, the server will obtain the pre-set minimum batch specification of the goods to be transported so that the goods to be transported can be divided into several units of goods to be transported, and then according to the above allocation steps, each unit of goods to be transported is allocated and processed to determine the second allocated cargo ship corresponding to one or more units of goods to be transported. The second allocated cargo ship is a cargo ship to which the goods unit to be transported is allocated. At this time, the second allocated cargo ship counted is used as the first allocated cargo ship. If the goods to be transported cannot be transported in batches or cannot be completely transported after being transported in batches, the server can generate a manual intervention prompt message and send it to the user terminal so that the user corresponding to the user terminal intervenes to adjust the transportation of the goods to be transported and specify the first allocated cargo ship for the goods. The user terminal can be understood as a mobile phone, computer or other device of a port and shipping logistics manager, and the manual intervention prompt message can be text or sound information, which is not specifically limited in this application.

[0083] Through the above scheme, the efficiency and accuracy of cargo distribution can be improved, thereby meeting customer needs and reducing transportation costs.

[0084] S104, the server determines the corresponding evaluation score of each port based on each initial arrival time node, and compares the evaluation score of each port with the preset control evaluation threshold.

[0085] Among them, the port assessment score is based at least on the berth urgency, logistics and transportation traffic conditions, and the matching degree of the arrival time node corresponding to the initial arrival time node.

[0086] In the embodiment of the present application, based on each initial arrival time node, the corresponding port evaluation score is determined, specifically including:

[0087] According to the initial arrival time node, determine the corresponding berth occupancy rate and the number of ships waiting for berths to calculate the berth urgency of the stopover port at the initial arrival time node. Match the initial arrival time node with the preset traffic condition list to determine the road congestion index, average transportation time, and average transportation cost of the urban network corresponding to the stopover port to calculate the logistics and transportation traffic conditions. Calculate the time difference between the initial arrival time node and the preset port operation time, and determine the arrival time node matching degree based on the time difference and the preset time difference threshold and the maximum allowable time difference. The weighted product value of the berth urgency, logistics and transportation traffic conditions, and arrival time node matching degree is used as the port evaluation score of the corresponding stopover port at the initial arrival time node.

[0088] In other words, this application comprehensively considers the three dimensions of berth urgency, logistics and transportation traffic conditions, and arrival time node matching, and evaluates the port assessment score of the initial arrival time node, so as to comprehensively evaluate the rationality of the transportation plan. This application can collect the berth occupancy and the number of ships waiting for berths of each port in a certain period of time as historical sample data, so as to establish a neural network model that identifies the berth occupancy rate and the number of ships waiting for berths corresponding to different times. The server inputs the initial arrival time node and the port of stay into the neural network model, and can obtain the berth occupancy rate and the number of ships waiting for berths output by the model, and then calculates the berth urgency P:

[0089]

[0090] Among them, ω1 and ω2 are preset weight coefficients, ω1+ω2=1; O is the berth occupancy rate; W is the number of ships waiting for berths; C is the berth capacity, that is, the maximum number of ships that the port can accommodate at the same time.

[0091] In the embodiment of the present application, the initial arrival time node is matched with the preset traffic condition list to determine the road congestion index, average transportation time, and average transportation cost of the city network corresponding to the stopover port, specifically including:

[0092] According to the cargo transport attributes of the cargo loaded and unloaded at the port of call, the corresponding types of transport vehicles are determined. According to the types of transport vehicles and the preset traffic impact list corresponding to the urban network, the road congestion index, average transport time, and average transport cost are determined. Among them, the preset traffic impact list includes the road congestion index, average transport time, and average transport cost of different types of transport vehicles arriving at different locations at different times.

[0093] The server can match the type of transport vehicle to be transported for loading and unloading at the port of call according to the transport attributes of the goods. This application can establish a preset traffic impact list of the impact of different transport vehicle types on urban network traffic based on urban traffic data in advance, so as to obtain the road congestion index, average transportation time, and average transportation cost through the preset traffic impact list. Then calculate the logistics transportation traffic status T c :

[0094]

[0095] Among them, ω3, ω4 and ω5 are preset weight coefficients, ω3+ω4+ω5=1; J is the road congestion index, between 0 and 1, 0 means no congestion at all, 1 means complete congestion; T t is the average transportation time, that is, the average time required for goods to travel from the port to the destination; C t is the average transportation cost, which is the average cost of transporting goods from the port to the destination.

[0096] Then, the server can calculate the time difference ΔT between the initial arrival time node and the preset port operation time, and determine the arrival time node matching degree according to the time difference and the preset time difference threshold and the maximum allowable time difference value, including:

[0097] If the time difference is less than or equal to the preset time difference threshold, the arrival time node matching degree is determined to be 1. If the time difference is greater than the preset time difference threshold and less than or equal to the maximum allowable time difference value, the arrival time node matching degree is determined to be Among them, T th is the preset time difference threshold, ΔT is the time difference, T max is the maximum allowable time difference. If the time difference is greater than the maximum allowable time difference, the arrival time node matching degree is determined to be 0.

[0098] Arrival time node matching degree T m The formula is as follows:

[0099]

[0100] Specifically, if the time difference is within the time difference threshold range, the matching degree is 1; if the time difference exceeds the threshold but is still within the maximum allowable value range, the matching degree gradually decreases; if the time difference exceeds the maximum allowable value, the matching degree is zero.

[0101] The server will then calculate the port assessment score using the following formula:

[0102]

[0103] Among them, α, β, and γ are weight coefficients of berth urgency, logistics and transportation traffic conditions, and arrival time node matching, which are set by the user according to actual use and are not specifically limited in this application; ε, δ, and ρ are adjustment parameters used to adjust the sensitivity and stability of the formula, which are set by the user according to actual use and are not specifically limited in this application.

[0104] S105, the server updates the initial arrival time node according to the comparison results of the evaluation scores of each port with the preset control evaluation threshold and the preset correction rules to adjust the transportation plan and loading and unloading plan.

[0105] In the embodiment of the present application, the initial arrival time node is updated according to the comparison result of each port evaluation score with the preset control evaluation threshold and the preset correction rule, specifically including:

[0106] When the port assessment score is less than the preset control assessment threshold, determine the time controllable interval for the first assigned cargo ship to arrive at the port of stay. Among them, the time controllable interval includes at least the initial arrival time node. According to the time controllable interval, generate a port assessment score curve corresponding to each controllable arrival time node. Determine the time nodes in the port assessment score curve that are greater than or equal to the preset control assessment threshold, and add the time nodes to the sequence of arrival time nodes to be selected in order from small to large according to the difference between the time nodes and the initial arrival time nodes. Send the sequence of arrival time nodes to be selected to the user terminal, so that based on the user's operation of selecting the time node, the selected arrival time node to be selected is updated to the initial arrival time node, so as to adjust the transportation plan and loading and unloading plan according to the updated initial arrival time node.

[0107] In other words, this application can compare the port assessment score with the preset control assessment threshold, and different comparison results can correspond to different preset correction rules, thereby updating the initial arrival time node. The preset control assessment threshold can be set during actual use, and this application does not make specific restrictions on this. When the port assessment score is less than the preset control assessment threshold, it means that the initial arrival time node needs to be corrected. The server will establish a plane rectangular coordinate system with time as the horizontal axis and the port assessment score as the vertical axis, and at the same time obtain the controllable time interval for the first assigned cargo ship to arrive at the port of stay in the preset database.

[0108] Among them, the time controllable interval can be understood as the time period before and after the initial arrival time node, and the time interval of the initial arrival time node can be changed by adjusting the speed of the cargo ship and / or the departure time of the cargo ship. For example, the initial arrival time node is 8:00:00, and the first assigned cargo ship adjusts the speed of the cargo ship and / or the departure time of the cargo ship, and can arrive at 7:15:00 at the earliest and 9:00:00 at the latest. Then [7:15:00, 9:00:00] is a time controllable interval. The server can calculate the port evaluation score corresponding to each time node in the time controllable interval, thereby establishing a port evaluation score curve in the plane direct coordinate system.

[0109] The server compares the port assessment score curve with the preset control assessment threshold, determines the curve portion whose ordinate value is greater than or equal to the preset control assessment threshold, and determines the time node corresponding to the curve portion. According to the difference between the time node and the initial arrival time node, the time node is added to the sequence of arrival time nodes to be selected. For example, the arrival time nodes to be selected include 7:31:00, 7:45:00, 8:05:00, 8:30:00, and the sequence of arrival time nodes to be selected is [8:05:00, 7:45:00, 7:31:00, 8:30:00]. That is, the smaller the absolute value of the difference with the initial arrival time node, the closer the time to the initial arrival time node, and the closer it is in the sequence of arrival time nodes to be selected. Subsequently, the server sends the sequence of arrival time nodes to be selected to the user terminal, and the user can select a certain arrival time node to be selected in the sequence as the initial arrival time node, thereby adjusting the transportation plan and loading and unloading plan by adjusting the speed of the cargo ship and / or the departure time of the cargo ship, and realizing intelligent control of port and shipping logistics.

[0110] If the port assessment score is not less than the preset control assessment threshold, there is no need to adjust or update the initial arrival time node.

[0111] In addition, since a first allocated cargo ship may have to berth at multiple ports, the present application can consider multiple ports of call at the same time and coordinate transportation plans and loading and unloading plans synchronously by combining the port assessment scores of each port of call, such as weighted average, and comparing them with the preset control assessment threshold.

[0112] Through the above scheme, this application can generate a transportation route network and a collection of cargo transportation time periods in combination with port logistics information, realize transportation route planning and provide clear time limits, and flexibly allocate cargo ships for cargo. Under the comprehensive multi-dimensional factors, the initial arrival time node set for the cargo ship is dynamically evaluated to adjust the initial arrival time node to optimize the transportation plan and improve loading and unloading efficiency and transportation speed. It solves the problem that port and shipping logistics management is too dependent on manual experience, the level of intelligence is not high, and a series of problems brought to port and shipping logistics transportation, berth management, and transportation, and improves the user experience of port and shipping logistics.

[0113] Figure 2 A schematic diagram of the structure of a port and shipping logistics intelligent management and control system provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the port and shipping logistics intelligent management and control system 200 includes:

[0114] The acquisition module 201 is used to obtain the port and shipping logistics information from the cloud. Among them, the port and shipping logistics information at least includes cargo transaction information, waterway conditions, traffic flow, and weather conditions that rely on inland waterway transportation. The first determination module 202 is used to determine the transportation route network and the cargo transportation time period set based on the port and shipping logistics information and the preset logistics transportation allocation model. The allocation module 203 is used to allocate each cargo to be transported to the corresponding one or more first allocation cargo ships according to the transportation route network and the cargo transportation time period set and the preset DP algorithm, and determine the initial arrival time node of the first allocation cargo ship at each stop port. The second determination module 204 is used to determine the corresponding evaluation score of each port based on each initial arrival time node, so as to compare the evaluation score of each port with the preset control evaluation threshold. Among them, the port evaluation score is obtained based on at least the berth urgency corresponding to the initial arrival time node, the logistics transportation traffic conditions, and the arrival time node matching degree. The update module 205 is used to update the initial arrival time node according to the comparison result of the evaluation score of each port with the preset control evaluation threshold and the preset correction rule, so as to adjust the transportation plan and loading and unloading plan.

[0115] The first determining module 202 is specifically configured to:

[0116] The port and shipping logistics information is used as a model input parameter and input into a preset logistics transportation allocation model to determine the transportation route network according to the model output result. The preset logistics transportation allocation model is a pre-trained multi-objective optimization model. The multi-objective optimization model includes a comprehensive objective function with at least transportation cost and transportation time as objective functions. According to the transportation route network, the preset transportation time division standard, and the cargo transaction information, the corresponding goods to be transported are clustered to obtain sets of cargo transportation time periods corresponding to different cargo attribute sets. A cargo transportation time period set includes one or more goods to be transported corresponding to the same cargo attribute set and one or more corresponding transportation time periods. The cargo attribute set is obtained based on clustering the cluster feature vectors corresponding to the transportation route network, the preset transportation time division standard, and the cargo transaction information.

[0117] The allocation module 203 is specifically used for:

[0118] According to the transport route network and the set of cargo transport time periods, and the preset DP algorithm, each achievable transport route and each achievable transport time period corresponding to the cargo to be transported are traversed to generate each achievable transport tuple. Each achievable transport tuple is matched with the preset port cargo ship berthing list to generate a sequence of cargo ships to be allocated for transport according to the matching result. Among them, the preset port cargo ship berthing list includes several cargo ship labels to be allocated, routes and port planned berthing time. Based on the cargo ship full load rate, cargo transportation attributes and preset allocation conditions, according to the order of the cargo ship sequence to be allocated, it is judged in sequence whether the cargo to be transported can be allocated to the current cargo ship. Among them, the cargo ship full load rate includes volume full load rate and weight full load rate. The cargo transportation attributes include at least cargo volume and cargo weight. The preset allocation conditions include at least that the cargo transportation attribute is in the remaining loadable capacity interval. The remaining loadable capacity interval is obtained based on the cargo ship full load rate and the maximum load capacity of the cargo ship, including the remaining volume loading rate sub-interval and the remaining weight loading sub-interval. If so, according to the cargo transportation attributes, the cargo ship full load rate of the current cargo ship is updated, and the current cargo ship is used as the first allocated cargo ship. Otherwise, it is determined whether the cargo to be transported can be allocated to the next cargo ship until the first allocated cargo ship is determined. According to the historical navigation record of the first allocated cargo ship, the corresponding initial arrival time nodes are determined.

[0119] The system can also:

[0120] In the case that there is no first allocated cargo ship to be allocated to the cargo to be transported, determine whether the cargo to be transported is cargo that can be transported in batches. If so, divide the cargo to be transported into multiple batches of cargo units to be transported according to the preset minimum batch specifications corresponding to the cargo to be transported, and judge in turn whether each cargo unit to be transported can be allocated to the current cargo ship, until all cargo units to be transported are allocated to multiple cargo ships in the sequence of cargo ships to be allocated, so that the cargo ship to which the cargo unit to be transported is allocated is used as the first allocated cargo ship. Otherwise, generate a manual intervention prompt message and send it to the user terminal so that the first allocated cargo ship to be transported is manually designated.

[0121] The second determining module 204 is specifically configured to:

[0122] According to the initial arrival time node, determine the corresponding berth occupancy rate and the number of ships waiting for berths to calculate the berth urgency of the stopover port at the initial arrival time node. Match the initial arrival time node with the preset traffic condition list to determine the road congestion index, average transportation time, and average transportation cost of the urban network corresponding to the stopover port to calculate the logistics and transportation traffic conditions. Calculate the time difference between the initial arrival time node and the preset port operation time, and determine the arrival time node matching degree based on the time difference and the preset time difference threshold and the maximum allowable time difference. The weighted product value of the berth urgency, logistics and transportation traffic conditions, and arrival time node matching degree is used as the port evaluation score of the corresponding stopover port at the initial arrival time node.

[0123] The second determining module 204 is further configured to:

[0124] According to the cargo transport attributes of the cargo loaded and unloaded at the port of call, the corresponding types of transport vehicles are determined. According to the types of transport vehicles and the preset traffic impact list corresponding to the urban network, the road congestion index, average transport time, and average transport cost are determined. Among them, the preset traffic impact list includes the road congestion index, average transport time, and average transport cost of different types of transport vehicles arriving at different locations at different times.

[0125] The second determining module 204 is further configured to:

[0126] If the time difference is less than or equal to the preset time difference threshold, the arrival time node matching degree is determined to be 1. If the time difference is greater than the preset time difference threshold and less than or equal to the maximum allowable time difference value, the arrival time node matching degree is determined to be Among them, T th is the preset time difference threshold, ΔT is the time difference, and δ is the maximum allowable time difference. If the time difference is greater than the maximum allowable time difference, the arrival time node matching degree is determined to be 0.

[0127] The update module 205 is specifically used for:

[0128] When the port assessment score is less than the preset control assessment threshold, determine the time controllable interval for the first assigned cargo ship to arrive at the port of stay. Among them, the time controllable interval includes at least the initial arrival time node. According to the time controllable interval, generate a port assessment score curve corresponding to each controllable arrival time node. Determine the time nodes in the port assessment score curve that are greater than or equal to the preset control assessment threshold, and add the time nodes to the sequence of arrival time nodes to be selected in order from small to large according to the difference between the time nodes and the initial arrival time nodes. Send the sequence of arrival time nodes to be selected to the user terminal, so that based on the user's operation of selecting the time node, the selected arrival time node to be selected is updated to the initial arrival time node, so as to adjust the transportation plan and loading and unloading plan according to the updated initial arrival time node.

[0129] Figure 3 A schematic diagram of the structure of a port and shipping logistics intelligent management and control device provided in an embodiment of the present application, such as Figure 3 As shown, the device includes:

[0130] At least one processor. And a memory in communication with the at least one processor. The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0131] Obtain port and shipping logistics information from the cloud. Among them, port and shipping logistics information at least includes cargo transaction information, waterway conditions, traffic flow, and weather conditions that rely on inland waterway transportation. Based on the port and shipping logistics information and the preset logistics transportation allocation model, determine the transportation route network and the cargo transportation time period set. According to the transportation route network and the cargo transportation time period set and the preset DP algorithm, each cargo to be transported is respectively allocated to one or more corresponding first allocated cargo ships, and the initial arrival time node of the first allocated cargo ship at each stopover port is determined. Based on each initial arrival time node, determine the corresponding evaluation score of each port to compare the evaluation score of each port with the preset control evaluation threshold. Among them, the port evaluation score is obtained at least based on the berth urgency corresponding to the initial arrival time node, the logistics transportation traffic conditions, and the arrival time node matching degree. According to the comparison results of the evaluation scores of each port with the preset control evaluation threshold and the preset correction rules, update the initial arrival time node to adjust the transportation plan and loading and unloading plan.

[0132] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system and device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0133] The system and equipment provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and equipment also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the system and equipment will not be repeated here.

[0134] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0135] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for intelligent management and control of port and shipping logistics, characterized in that: The method comprises: Obtaining port and shipping logistics information from the cloud; wherein the port and shipping logistics information at least includes cargo transaction information, waterway conditions, traffic flow, and weather conditions that rely on inland waterway transportation; Based on the port and shipping logistics information and the preset logistics transportation allocation model, determine the transportation route network and the cargo transportation time period set; According to the transport route network, the cargo transport time period set and the preset DP algorithm, each cargo to be transported is respectively allocated to one or more corresponding first allocated cargo ships, and the initial arrival time node of the first allocated cargo ship at each stop port is determined; Based on each of the initial arrival time nodes, determine the corresponding port assessment score to compare each of the port assessment scores with a preset control assessment threshold; wherein the port assessment score is obtained based at least on the berth urgency, logistics and transportation traffic conditions, and arrival time node matching degree corresponding to the initial arrival time node; According to the comparison results of the assessment scores of each port with the preset control assessment threshold and the preset correction rules, the initial arrival time node is updated to adjust the transportation plan and loading and unloading plan.

2. According to claim 1, a method for intelligent management and control of port and shipping logistics is characterized in that: Based on the port and shipping logistics information and the preset logistics transportation allocation model, the transportation route network and the cargo transportation time period set are determined, specifically including: The port and shipping logistics information is used as a model input parameter and input into the preset logistics transportation allocation model to determine the transportation route network according to the model output result; wherein the preset logistics transportation allocation model is a pre-trained multi-objective optimization model; the multi-objective optimization model includes a comprehensive objective function with at least transportation cost and transportation time as objective functions; According to the transportation route network, the preset transportation time period division standard, and the cargo transaction information, the corresponding goods to be transported are clustered to obtain sets of cargo transportation time periods corresponding to different cargo attribute sets; wherein, one cargo transportation time period set includes one or more goods to be transported corresponding to the same cargo attribute set and one or more transportation time periods corresponding thereto; the cargo attribute set is obtained based on clustering the cluster feature vectors corresponding to the transportation route network, the preset transportation time period division standard, and the cargo transaction information.

3. According to claim 1, a method for intelligent management and control of port and shipping logistics is characterized in that: According to the transportation route network, the cargo transportation time period set, and the preset DP algorithm, each cargo to be transported is respectively allocated to one or more corresponding first allocation cargo ships, and the initial arrival time node of the first allocation cargo ship at each stopover port is determined, specifically including: According to the transportation route network, the cargo transportation time period set, and the preset DP algorithm, traverse each achievable transportation route and each achievable transportation time period corresponding to the cargo to be transported, and generate each achievable transportation tuple; Matching each of the achievable transport tuples with a preset port cargo ship berthing list to generate a sequence of transport cargo ships to be allocated according to the matching results; wherein the preset port cargo ship berthing list includes a number of transport cargo ship labels to be allocated, routes and port planned berthing times; Based on the cargo ship full load rate, cargo transportation attributes and preset allocation conditions, in the order of the sequence of cargo ships to be allocated, it is judged in turn whether the cargo to be transported can be allocated to the current cargo ship; wherein the cargo ship full load rate includes volume full load rate and weight full load rate; the cargo transportation attributes include at least cargo volume and cargo weight; the preset allocation conditions include at least that the cargo transportation attributes are in the remaining loadable capacity interval; the remaining loadable capacity interval is obtained based on the cargo ship full load rate and the maximum load capacity of the cargo ship, and includes a remaining volume loading rate sub-interval and a remaining weight loading sub-interval; If yes, update the cargo ship full load rate of the current cargo ship according to the cargo transportation attribute, and use the current cargo ship as the first allocated cargo ship; otherwise, determine whether the cargo to be transported can be allocated to the next cargo ship until the first allocated cargo ship is determined; According to the historical sailing record of the first allocated cargo ship, the corresponding initial arrival time nodes are determined.

4. The intelligent management and control method for port and shipping logistics according to claim 3 is characterized in that: The method further comprises: In the case that there is no first allocated cargo ship that can allocate the cargo to be transported, determining whether the cargo to be transported is cargo that can be transported in batches; If so, the cargo to be transported is divided into multiple batches of cargo units to be transported according to the preset minimum batch specification corresponding to the cargo to be transported, and each of the cargo units to be transported is judged in turn whether it can be allocated to the current cargo ship, until all the cargo units to be transported are allocated to multiple cargo ships in the sequence of cargo ships to be allocated, so that the cargo ship to which the cargo units to be transported are allocated is used as the first allocated cargo ship; Otherwise, a manual intervention prompt message is generated and sent to the user terminal so that the first allocated cargo ship for the cargo to be transported is manually designated.

5. The intelligent management and control method for port and shipping logistics according to claim 1 is characterized in that: Based on each of the initial arrival time nodes, the corresponding port assessment scores are determined, specifically including: According to the initial arrival time node, determining the corresponding berth occupancy rate and the number of ships waiting for berths, so as to calculate the berth urgency of the stop port at the initial arrival time node; Matching the initial arrival time node with a preset traffic condition list to determine the road congestion index, average transportation time, and average transportation cost of the city network corresponding to the stopover port to calculate the logistics transportation traffic condition; Calculating the time difference between the initial arrival time node and the preset port operation time, and determining the matching degree of the arrival time node according to the time difference, the preset time difference threshold, and the maximum allowable time difference value; The weighted product value of the berth urgency, the logistics transportation traffic conditions and the arrival time node matching degree is used as the port evaluation score of the corresponding stopover port at the initial arrival time node.

6. The intelligent management and control method for port and shipping logistics according to claim 5 is characterized in that: Matching the initial arrival time node with a preset traffic condition list to determine the road congestion index, average transportation time, and average transportation cost of the city network corresponding to the stopover port, specifically including: Determine the corresponding types of transport vehicles according to the cargo transport attributes of the cargo loaded and unloaded at the stop port; The road congestion index, the average transportation time, and the average transportation cost are determined according to the transport vehicle type and the preset traffic impact list corresponding to the urban network; wherein the preset traffic impact list includes the road congestion index, the average transportation time, and the average transportation cost of different transport vehicle types arriving at different locations at different times.

7. The intelligent management and control method for port and shipping logistics according to claim 5 is characterized in that: Determining the matching degree of the arrival time node according to the time difference, a preset time difference threshold, and a maximum allowable time difference value, specifically includes: When the time difference is less than or equal to the preset time difference threshold, determining that the arrival time node matching degree is 1; When the time difference is greater than the preset time difference threshold and less than or equal to the maximum allowable time difference value, the arrival time node matching degree is determined to be Among them, T th is the preset time difference threshold, ΔT is the time difference, and δ is the maximum allowable value of the time difference; When the time difference is greater than the maximum allowed value of the time difference, it is determined that the arrival time node matching degree is 0.

8. The intelligent management and control method for port and shipping logistics according to claim 1 is characterized in that: According to the comparison results of the port assessment scores with the preset control assessment thresholds and the preset correction rules, the initial arrival time node is updated, specifically including: When the port evaluation score is less than the preset control evaluation threshold, determining a controllable time interval for the first allocated cargo ship to arrive at the stop port; wherein the controllable time interval at least includes the initial arrival time node; According to the controllable time interval, generating a port evaluation score curve corresponding to each controllable arrival time node; Determine the time nodes in the port assessment score curve that are greater than or equal to the preset control assessment threshold, and add the time nodes to the sequence of arrival time nodes to be selected in order of the difference between the time nodes and the initial arrival time nodes from small to large; The sequence of arrival time nodes to be selected is sent to the user terminal, so that based on the user's operation of selecting the time node, the selected arrival time node to be selected is updated to the initial arrival time node, so as to adjust the transportation plan and the loading and unloading plan according to the updated initial arrival time node.

9. An intelligent management and control system for port and shipping logistics, characterized in that: The system comprises: An acquisition module, used to acquire port and shipping logistics information from the cloud; wherein the port and shipping logistics information at least includes cargo transaction information, waterway conditions, traffic flow, and weather conditions that rely on inland waterway transportation; A first determination module is used to determine a transportation route network and a set of cargo transportation time periods based on the port and shipping logistics information and a preset logistics transportation allocation model; An allocation module is used to allocate each cargo to be transported to one or more corresponding first allocation cargo ships according to the transportation route network, the cargo transportation time period set, and a preset DP algorithm, and determine the initial arrival time node of the first allocation cargo ship at each stopover port; A second determination module is used to determine the corresponding port evaluation score based on each of the initial arrival time nodes, so as to compare the port evaluation score with a preset control evaluation threshold; wherein the port evaluation score is obtained based at least on the berth urgency, logistics and transportation traffic conditions, and arrival time node matching degree corresponding to the initial arrival time node; The updating module is used to update the initial arrival time node according to the comparison result of each port evaluation score with the preset control evaluation threshold and the preset correction rule to adjust the transportation plan and the loading and unloading plan.

10. An intelligent control device for port and shipping logistics, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method for intelligent management and control of port and shipping logistics as described in any one of claims 1 to 8 above.

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