A method and system for generating a port dispatching plan based on digitization

Abstract

The present invention relates to the technical field of port dispatching, and in particular to a method and system for generating a port dispatching scheme based on digitization, the method comprising the following steps: collecting historical port environment data and historical operation data, and using the collected data to construct a port dispatching data resource pool; constructing a network model of port operation, and obtaining a state influence coefficient set of port nodes in the network model according to the port dispatching data resource pool; determining a backup dispatching scheme based on the maximum similarity matching principle according to the real-time port environment data, real-time operation data and the port dispatching data resource pool; adjusting the backup dispatching scheme according to the state influence coefficient set, and finally obtaining a real-time port dispatching scheme. The present invention improves the scientificity and intelligent level of port dispatching, can improve the operational efficiency of ports, and provides more options for the generation of port dispatching schemes.

Description

Technical Field

[0001] The present invention relates to the technical field of port dispatching, and in particular to a method and system for generating a port dispatching plan based on digitization. Background Art

[0002] Traditional port cargo transportation scheduling mainly relies on manual experience and simple rule-based judgment. This approach is often difficult to achieve optimal resource allocation and maximize transportation efficiency when faced with a complex and changing port operating environment.

[0003] Considering that the entry and exit of ships is a critical part of the normal operation of the port, the existing port scheduling methods mostly focus on scheduling ships in the port, and to a certain extent improve the port's operational efficiency and safety. However, the existing comprehensive scheduling solutions for equipment in the port are relatively few and lack real-time performance, so that the port scheduling solution is difficult to accurately fit the actual situation of the port, which to a certain extent reduces the port's operational efficiency. Summary of the invention

[0004] In view of the defects in the prior art, the present invention provides a method and system for generating a port scheduling plan based on digitization.

[0005] In order to achieve the above-mentioned purpose, in the first aspect, the present invention provides a method for generating a port scheduling scheme based on digitization, the method comprising the following steps: collecting historical port environment data and historical operation data, and using the collected data to construct a port scheduling data resource pool; constructing a network model of port operation, and obtaining a state influence coefficient set of port nodes in the network model according to the port scheduling data resource pool; determining a backup scheduling scheme based on the maximum similarity matching principle according to the real-time port environment data, real-time operation data and the port scheduling data resource pool; adjusting the backup scheduling scheme according to the state influence coefficient set, and finally obtaining a real-time port scheduling scheme. The present invention improves the scientificity and intelligence level of port scheduling, can improve the operational efficiency of ports, and provides more options for the generation of port scheduling schemes.

[0006] Optionally, the historical environmental data of the port include historical temperature of the port, historical humidity of the port, historical wind speed of the port, historical rainfall of the port and historical hydrological data of the port, the historical hydrological data of the port include historical wave height of the port and historical water flow speed of the port, the historical operation data specifically include equipment operation data and cargo handling volume, the equipment operation data include actual equipment operation time and theoretical equipment operation time.

[0007] Furthermore, the present invention provides data support for generating reliable port scheduling solutions by collecting complete port historical environmental data, historical operation data and equipment operation data.

[0008] Optionally, the collecting of historical port environment data and historical operation data and using the collected data to construct a port dispatching data resource pool comprises the following steps:

[0009] Collecting the port historical environment data and the historical operation data and performing preprocessing to obtain multiple sets of accurate port historical environment data and accurate historical operation data;

[0010] Dividing the port operation environment level, and then using the historical operation precise data under the same port operation environment level to form a historical operation data subset according to the historical environment precise data;

[0011] The port scheduling data resource pool is constructed using the historical operation data subsets under different port operation environment levels.

[0012] Furthermore, the present invention divides historical operation data subsets based on the port operation environment level, and then generates a port scheduling plan by considering the impact of the environment on the port operation, thereby improving the accuracy and reliability of the port scheduling plan.

[0013] Optionally, the step of constructing a network model of port operations and obtaining a state influence coefficient set of port nodes in the network model according to the port scheduling data resource pool comprises the following steps:

[0014] Taking each device in the port as the port node, and determining the priority and relevance of the port node according to the flow direction of goods, and then constructing the network model;

[0015] Calculate the action efficiency of each port node in the network model under each group of the historical operation precise data in the historical operation data subset to obtain an action efficiency data subset;

[0016] A state influence coefficient set of each port node is obtained according to the action efficiency data subset.

[0017] Furthermore, the present invention demonstrates the interaction relationship between various devices inside the port by constructing a port operation network model and obtaining a set of state influence coefficients of port nodes, providing a scientific basis for subsequent adjustment and generation of port scheduling plans.

[0018] Optionally, the step of acquiring a state influence coefficient set of each port node according to the action efficiency data subset comprises the following steps:

[0019] Recording a certain port node as a target port node, and recording other port nodes at the same level and the next level of the target port node as associated nodes;

[0020] Numbering the associated nodes, and then calculating the state influence coefficient of the target port node on each of the associated nodes in sequence according to the action efficiency data subset, to obtain a state influence coefficient subset of the target port node;

[0021] The state influence coefficient subset is used to form the state influence coefficient set of the target port node, and then the state influence coefficient set of all the port nodes is obtained.

[0022] Furthermore, the present invention obtains a subset of state influence coefficients of port nodes based on a subset of action efficiency data, taking into account the impact of environmental factors on the state influence coefficients between various port nodes, and can more accurately reflect the mutual influence between internal equipment in the port, providing strong support for generating and optimizing port scheduling plans.

[0023] Optionally, the state influence coefficient satisfies the following relationship:

[0024]

[0025] in, is the state influence coefficient of the target port node on the i-th associated node, n is the logarithm of the action efficiency in the action efficiency data subset, and two adjacent groups of action efficiencies in the action efficiency data subset are a pair of action efficiencies, is the action efficiency of the i-th associated node in the j+1-th group of action efficiencies, is the action efficiency of the i-th associated node in the j-th group of action efficiencies, is the action efficiency of the target port node in the j+1th group of action efficiencies, is the action efficiency of the target port node in the jth group of action efficiency.

[0026] Furthermore, the state influence coefficient quantifies the mutual influence between port nodes based on the changes in action efficiency, which is conducive to predicting the changes in the action efficiency of other port nodes according to the changes in the action efficiency of a certain port node, and then quickly adjusting and generating port scheduling plans, thereby improving the real-time performance of port scheduling plans.

[0027] Optionally, the step of determining the backup scheduling scheme based on the maximum similarity matching principle according to the port real-time environmental data, the real-time operation data and the port scheduling data resource pool comprises the following steps:

[0028] Determining the real-time port operation environment level according to the real-time port environment data, and calculating the real-time action efficiency of each of the port nodes according to the real-time operation data;

[0029] Recording the action efficiency data subset under the real-time port operation environment level as a target efficiency subset;

[0030] In the target efficiency subset, the equipment operation plan corresponding to a group of action efficiencies with the greatest similarity to the real-time action efficiency is used as the backup scheduling plan.

[0031] Furthermore, the present invention determines the backup scheduling scheme based on the maximum similarity matching principle, thereby improving the practicality and feasibility of the port scheduling scheme.

[0032] Optionally, the step of adjusting the backup scheduling scheme according to the state influence coefficient set to finally obtain a real-time port scheduling scheme comprises the following steps:

[0033] In the state influence coefficient set, normalizing the state influence coefficient subset corresponding to the target efficiency subset to obtain a normalized state influence coefficient subset;

[0034] The difference between the actual operation time of the equipment in the backup scheduling scheme and the theoretical operation time of the current equipment is recorded as the equipment operation difference, and the port node with the largest equipment operation difference is recorded as the hub node;

[0035] Adjusting the action efficiency of the hub node, and adjusting the action efficiency of the associated nodes of the hub node using a state update function according to the normalized state influence coefficient subset;

[0036] Calculate the predicted operation time of each device according to the adjusted action efficiency of the hub node and its associated nodes;

[0037] Calculate the sum of the differences between the predicted running time of each device and the theoretical running time of the current device, and record it as the running time error;

[0038] The hub node is continuously selected and the action efficiency of the hub node and its associated nodes is adjusted until the set number of iterations is reached, and the equipment operation plan corresponding to the minimum operating time error is used as the port scheduling plan.

[0039] Furthermore, the present invention minimizes the equipment operation time error by continuously selecting and adjusting the action efficiency of the hub node and its associated nodes, thereby obtaining the optimal scheduling plan, ensuring that the port scheduling plan is close to the actual situation of the port, with high accuracy and real-time performance, and then performing real-time scheduling of port equipment to resist the impact of variable factors in the port on port operations and improve port operation efficiency.

[0040] Optionally, the state update function satisfies the following relationship:

[0041]

[0042] in, Update the action efficiency value of the i-th associated node of the hub node, is the action efficiency of the i-th associated node of the hub node, is the normalized state influence coefficient of the hub node on the i-th associated node, is the efficiency of the hub node after adjustment, is the unregulated efficiency of the hub node's actions.

[0043] Furthermore, the state update function of the present invention is simple and easy to implement. When adjusting the action efficiency of the hub node, the action efficiency of its associated nodes can be quickly and adaptively adjusted through the state update function, thereby flexibly adjusting the port scheduling plan according to actual conditions.

[0044] In the second aspect, the present invention provides a port scheduling scheme generation system based on digitization, the port scheduling scheme generation system based on digitization includes: a data acquisition device, a processor, a storage device and a data output device, the storage device includes a computer-readable storage medium, the computer-readable storage medium stores a computer program, the computer program includes program instructions, and the program instructions, when executed by the processor, enable the processor to implement a port scheduling scheme generation method based on digitization provided by the present invention. The system can stably run the method provided by the present invention, improve the efficiency of port scheduling scheme generation and the practicality of the method, and further improve the operational efficiency of the port. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A schematic diagram of a process of generating a port scheduling scheme based on digitization according to an embodiment of the present invention;

[0047] Figure 2 It is a schematic diagram of the framework of a digital-based port scheduling solution generation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0049] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0050] It should be noted in advance that, in an optional embodiment, except for independent explanations, the same symbols or letters appearing in all formulas have the same meanings and values.

[0051] In an alternative embodiment, see Figure 1 The present invention provides a method for generating a port scheduling scheme based on digitization, the method comprising the following steps:

[0052] S1. Collect historical environmental data and historical operation data of the port, and use the collected data to build a port scheduling data resource pool.

[0053] Wherein, step S1 specifically includes the following steps:

[0054] S11, collecting the port historical environment data and the historical operation data and performing preprocessing to obtain multiple groups of accurate port historical environment data and accurate historical operation data.

[0055] Specifically, in this embodiment, the port historical environmental data includes the port historical temperature, the port historical humidity, the port historical wind speed, the port historical rainfall and the port historical hydrological data, the port historical hydrological data includes the port historical wave height and the port historical water flow speed, the historical operation data specifically includes the equipment operation data and the cargo handling volume, and the equipment operation data includes the equipment actual operation time and the equipment theoretical operation time. The operation of preprocessing the port historical environmental data and historical operation data includes outlier removal and missing value filling. This embodiment provides data support for generating a reliable port scheduling plan by collecting complete port historical environmental data, historical operation data and equipment operation data.

[0056] More specifically, ports usually formulate equipment scheduling plans in advance and make the equipment in the port operate according to the formulated scheduling plans. The equipment operating time specified in the equipment scheduling plan is the theoretical operating time of the equipment.

[0057] Furthermore, in other optional embodiments, other types of port historical environmental data and historical operation data may also be selected, which are not listed here for the sake of brevity.

[0058] S12. Classify the port operation environment into levels, and then use the historical operation precise data under the same port operation environment level to form a historical operation data subset according to the historical environment precise data.

[0059] Specifically, in this embodiment, the port operation environment level is divided according to the impact of the port environment data on the port operation. The specific division method is shown in Table 1:

[0060] Table 1 Classification standards for port operating environment

[0061] Grade A (Excellent) The temperature and humidity are suitable, the rainfall, wind speed and water flow speed are small, and the wave height is low. That is, the temperature, humidity, rainfall, wind speed, water flow speed and wave height are all within the optimal range of port operations. The port can operate normally. The optimal range of temperature, humidity, rainfall, wind speed, water flow speed and wave height needs to be set according to the actual situation of the port with the help of expert experience. B-level (general) If one or more of the temperature, humidity, rainfall, wind speed, water flow speed and wave height deviate slightly from the optimal range of port operations, it will have a certain impact on the operation of the port. Take the port temperature as an example to explain under what circumstances each indicator deviates slightly from the optimal range of port operations: Assume that the lower limit of the optimal range of port temperature is min, the upper limit is max, and both min and max are not 0, and the port temperature is w. If w is greater than max, then when w / max is greater than 1 but less than 1.3, it means that the port temperature deviates slightly from the optimal range of port operations; if w is less than min, then when min / w is greater than 1 but less than 1.3, it means that the port temperature deviates slightly from the optimal range of port operations. Grade C (poor) One or more of the temperature, humidity, rainfall, wind speed, water flow speed and wave height seriously deviate from the optimal range of port operations, seriously affecting the normal operation of the port. Take the port temperature as an example to explain under what circumstances each indicator seriously deviates from the optimal range of port operations: if w is greater than max, then when w / max is greater than 1.3, it means that the port temperature seriously deviates from the optimal range of port operations; if w is less than min, then when min / w is greater than 1.3, it means that the port temperature seriously deviates from the optimal range of port operations.

[0062] More specifically, when classifying the port operating environment, the numerical division of various port historical environmental data needs to be set based on the infrastructure capacity and operating needs of different ports with the help of expert experience, so as to fit the actual situation of the port. For example, when the port operating environment level is A, how much rainfall is considered to be small rainfall, it is necessary to consider the drainage capacity of the port drainage facilities to set it.

[0063] Various equipment in the port are interrelated and influence each other, and changes in the environment will change the degree of mutual influence between various equipment. Therefore, this embodiment divides the historical operation data subsets based on the port operation environment level, and then considers the impact of the environment on the port operation to generate a port scheduling plan, thereby improving the accuracy and reliability of the port scheduling plan.

[0064] S13. Constructing the port dispatching data resource pool using the historical operation data subsets under different port operation environment levels.

[0065] Specifically, in this embodiment, historical operation data subsets under different port operation environment levels are used to form a port scheduling data resource pool. This embodiment divides historical operation data subsets based on the port operation environment level, and uses historical operation data subsets to form a port scheduling data resource pool, so as to generate a port scheduling plan considering the impact of the environment on port operations, thereby improving the accuracy and reliability of the port scheduling plan.

[0066] S2. Construct a network model for port operations, and obtain a set of state influence coefficients of port nodes in the network model according to the port scheduling data resource pool.

[0067] Wherein, step S2 specifically includes the following steps:

[0068] S21. Taking each device in the port as the port node, and determining the priority and relevance of the port node according to the flow direction of the goods, and then constructing the network model.

[0069] Specifically, in this embodiment, all key equipment in the port, such as cranes, transport vehicles, quay cranes, and gantry cranes, are identified, and these equipment are used as port nodes and can be assigned unique identifiers. According to the physical connection (such as logistics path) or logical connection (such as information sharing and scheduling dependency) between each key equipment, the edges between port nodes are established to form a network model.

[0070] More specifically, if there is an edge connecting port node A and port node B, and the goods flow from port node A to port node B, so that port node A and port node B form a direct superior-subordinate relationship, then port node A has a higher priority than port node B, and port node B is the next-level node of port node A. If there is an edge connecting port node C and port node A, and there is no direct superior-subordinate relationship between the two or they have equal status in the port, such as port node C and port node A are both forklifts, then port node C and port node A are nodes of the same level.

[0071] S22, calculating the action efficiency of each port node in the network model under each group of the historical operation precise data in the historical operation data subset, to obtain an action efficiency data subset.

[0072] Specifically, in this embodiment, the action efficiency of the port node is the quotient of the cargo handling volume of the equipment and the actual operating time of the equipment. A set of precise historical operation data in the historical operation data subset can be used to calculate the action efficiency of each port node under the set of precise historical operation data. The action efficiency of each port node under each set of precise historical operation data in the historical operation data subset is calculated to obtain multiple sets of action efficiencies, which then constitute an action efficiency data subset.

[0073] The present invention demonstrates the interaction relationship between various devices inside the port by constructing a port operation network model and obtaining a state influence coefficient set of port nodes, providing a scientific basis for subsequent adjustment and generation of port scheduling plans.

[0074] S23. Obtain a state influence coefficient set of each port node according to the action efficiency data subset.

[0075] Wherein, step S23 specifically includes the following steps:

[0076] S231. Record a certain port node as a target port node, and record other port nodes at the same level and the next level of the target port node as associated nodes.

[0077] S232, numbering the associated nodes, and then calculating the state influence coefficient of the target port node on each of the associated nodes in sequence according to the action efficiency data subset, to obtain a state influence coefficient subset of the target port node.

[0078] Specifically, in this embodiment, the state influence coefficient satisfies the following relationship:

[0079]

[0080] in, is the state influence coefficient of the target port node on the i-th associated node, n is the logarithm of the action efficiency in the action efficiency data subset, and two adjacent groups of action efficiencies in the action efficiency data subset are a pair of action efficiencies. is the action efficiency of the i-th associated node in the j+1-th group of action efficiencies, is the action efficiency of the i-th associated node in the j-th group of action efficiencies, is the action efficiency of the target port node in the j+1th group of action efficiencies, is the action efficiency of the target port node in the jth group of action efficiencies. The state influence coefficient quantifies the mutual influence between port nodes based on the change of action efficiency, which is conducive to predicting the change of action efficiency of other port nodes according to the change of action efficiency of a certain port node, and then quickly adjusting and generating port scheduling plans, improving the real-time performance of port scheduling plans.

[0081] Furthermore, this embodiment obtains a subset of state influence coefficients of port nodes based on a subset of action efficiency data, taking into account the impact of environmental factors on the state influence coefficients between various port nodes, and can more accurately reflect the mutual influence between internal equipment in the port, providing strong support for generating and optimizing port scheduling plans.

[0082] S233. Utilize the state influence coefficient subset to form the state influence coefficient set of the target port node, and then obtain the state influence coefficient set of all the port nodes.

[0083] S3. Determine the backup scheduling plan based on the maximum similarity matching principle according to the port's real-time environmental data, real-time operation data and port scheduling data resource pool.

[0084] Wherein, step S3 specifically includes the following steps:

[0085] S31. Determine the real-time port operation environment level according to the real-time port environment data, and calculate the real-time action efficiency of each of the port nodes according to the real-time operation data.

[0086] Specifically, in this embodiment, the content of this step can refer to the content described in step S12 and step S22, and will not be repeated here.

[0087] S32. Recording the action efficiency data subset under the real-time port operation environment level as a target efficiency subset.

[0088] S33. In the target efficiency subset, the equipment operation plan corresponding to a group of action efficiencies with the greatest similarity to the real-time action efficiency is used as the backup scheduling plan.

[0089] Specifically, in this embodiment, the Euclidean distance is used to determine the similarity between the real-time action efficiency of all equipment in the port and the action efficiency of each group in the target efficiency subset.

[0090] S4. Adjust the backup scheduling plan according to the state influence coefficient set to finally obtain a real-time port scheduling plan.

[0091] Wherein, step S4 specifically includes the following steps:

[0092] S41. In the state influence coefficient set, normalize the state influence coefficient subset corresponding to the target efficiency subset to obtain a normalized state influence coefficient subset.

[0093] Specifically, in this embodiment, the maximum and minimum value normalization processing method is used to normalize the state influence coefficient subset corresponding to the target efficiency subset, and the normalized state influence coefficient subset is expressed as , is the normalized state influence coefficient of the target port node on the i-th associated node, and m is the number of associated nodes of the target port node.

[0094] S42. Record the difference between the actual operation time of the equipment in the backup scheduling scheme and the current theoretical operation time of the equipment as the equipment operation difference, and record the port node with the largest equipment operation difference as the hub node.

[0095] S43, adjusting the action efficiency of the hub node, and at the same time adjusting the action efficiency of the associated nodes of the hub node using a state update function according to the normalized state influence coefficient subset.

[0096] Specifically, in this embodiment, the action efficiency of the hub node that is not adjusted in the backup scheduling scheme is taken as the first item, and the action efficiency of the hub node is changed according to the set tolerance to reduce the equipment operation difference of the hub node, and the state update function is used to adjust the action efficiency of its associated nodes. The state update function satisfies the following relationship:

[0097]

[0098] in, Update the action efficiency value of the i-th associated node of the hub node, is the action efficiency of the i-th associated node of the hub node, is the normalized state influence coefficient of the hub node on the i-th associated node, is the efficiency of the hub node after adjustment. The state update function of this embodiment is simple and easy to implement. When adjusting the action efficiency of the hub node, the action efficiency of its associated nodes can be adjusted quickly and adaptively through the state update function, thereby flexibly adjusting the port scheduling plan according to actual conditions.

[0099] More specifically, in this embodiment, the value of the tolerance is set to 1, that is, .

[0100] Furthermore, after adjusting the action efficiency of the associated nodes of the hub node, the action efficiency of other port nodes can be further adjusted according to the changes in the action efficiency of its associated nodes, thereby adaptively adjusting the action efficiency of as many port nodes as possible.

[0101] S44. Calculate the predicted operating time of each device based on the adjusted action efficiency of the hub node and its associated nodes.

[0102] Specifically, in this embodiment, the predicted operating time of each device is the quotient of the remaining cargo volume and the adjusted operation efficiency.

[0103] S45. Calculate the sum of the differences between the predicted running time of each device and the theoretical running time of the current device, and record it as the running time error.

[0104] Specifically, in this embodiment, the running time error satisfies the following relationship:

[0105]

[0106] Where T is the running time error, is the predicted running time of the kth device, is the current theoretical running time of the k-th device, where the k-th device is the k-th port node.

[0107] S46. Continuously select the hub node and adjust the action efficiency of the hub node and its associated nodes until the set number of iterations is reached, and use the equipment operation plan corresponding to the minimum operating time error as the port scheduling plan.

[0108] Specifically, in this embodiment, by repeatedly executing steps S42 to S45 at the set maximum number of iterations, multiple groups of adjusted port node action efficiencies and corresponding running time errors can be obtained, and then the equipment operation plan corresponding to the minimum running time error is used as the port scheduling plan, that is, the action efficiency of a group of port nodes corresponding to the minimum running time error is used as the final action efficiency of the port node, and the equipment at each port node is operated according to the corresponding final action efficiency. The final action efficiency V of the port node can be expressed as, , is the final action efficiency of the k-th device.

[0109] This embodiment continuously selects and adjusts the action efficiency of the hub node and its associated nodes so that the equipment operation time error is minimized, thereby obtaining the optimal scheduling plan, ensuring that the port scheduling plan is close to the actual situation of the port, with high accuracy and real-time performance, and then scheduling the port equipment in real time to resist the impact of variable factors in the port on port operations and improve port operation efficiency.

[0110] It should be noted that, in some cases, the actions described in the specification can be performed in a different order and still achieve the desired results. In this embodiment, the order of steps given is only to make the embodiment appear clearer and easier to explain, rather than to limit it.

[0111] In an alternative embodiment, see Figure 2The present invention also provides a port scheduling scheme generation system based on digitization, and the port scheduling scheme generation system based on digitization includes: a data acquisition device 1, a processor 2, a storage 3 and a data output device 4, the storage 3 includes a computer-readable storage medium, and the computer-readable storage medium stores a computer program. The computer program includes program instructions. When the program instructions are executed by the processor 3, the processor 3 implements a port scheduling scheme generation method based on digitization provided by the present invention, specifically executing the contents described in steps S1 to S4.

[0112] Specifically, in this embodiment, the data collection device 1 includes a digital display screen and a USB interface. Relevant personnel can input the collected port historical environmental data, historical operation data, port real-time environmental data and real-time operation data into the data collection device 1 through the digital display screen, and can also receive the port historical environmental data, historical operation data, port real-time environmental data and real-time operation data collected and stored by other devices through the USB interface. The final port dispatching plan will be output through the data output device 4.

[0113] In summary, the method first constructs a comprehensive port scheduling data resource pool by collecting and processing port historical data and real-time data, providing data support for generating reliable port scheduling plans. Then, the method constructs a port operation network model and obtains a state influence coefficient set to show the interaction relationship between the internal equipment of the port, providing a scientific basis for the subsequent adjustment and generation of port scheduling plans. Finally, the method adopts the maximum similarity matching principle and dynamic adjustment mechanism, and can flexibly formulate and adjust the port scheduling plan according to the actual situation, ensuring that the port scheduling plan can be close to the actual situation of the port, and then real-time scheduling of port equipment to resist the influence of variable factors in the port on port operations, and improve port operation efficiency. The method uses data-driven decision-making, which not only improves the scientificity and intelligence level of port scheduling, but also reduces the cost and risk of manual intervention in the process of generating port scheduling plans, which is conducive to improving the overall competitiveness of the port. In addition, the system provided by the present invention can stably operate the method provided by the present invention, improve the efficiency of generating port scheduling plans and the practicality of the method, and further improve the operation efficiency of the port.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for generating a port scheduling plan based on digitization, characterized in that: The steps include: Collect and pre-process the port's historical environmental data and historical operational data to obtain multiple sets of accurate port historical environmental data and accurate historical operational data; Dividing the port operation environment level, and then using the historical operation precise data under the same port operation environment level to form a historical operation data subset according to the historical environment precise data; Using the historical operation data subsets under different port operation environment levels to build a port scheduling data resource pool; Each device in the port is regarded as a port node, and the priority and relevance of the port nodes are determined according to the flow direction of the goods, thereby constructing a network model; Calculate the action efficiency of each port node in the network model under each group of the historical operation precise data in the historical operation data subset to obtain an action efficiency data subset; Recording a certain port node as a target port node, and recording other port nodes at the same level and the next level of the target port node as associated nodes; Numbering the associated nodes, and then calculating the state influence coefficient of the target port node on each of the associated nodes in sequence according to the action efficiency data subset, to obtain a state influence coefficient subset of the target port node; Using the state influence coefficient subset to form the state influence coefficient set of the target port node, and then obtaining the state influence coefficient set of all the port nodes; The state influence coefficient satisfies the following relationship: in, is the state influence coefficient of the target port node on the i-th associated node, n is the logarithm of the action efficiency in the action efficiency data subset, and two adjacent groups of action efficiencies in the action efficiency data subset are a pair of action efficiencies, is the action efficiency of the i-th associated node in the j+1-th group of action efficiencies, is the action efficiency of the i-th associated node in the j-th group of action efficiencies, is the action efficiency of the target port node in the j+1th group of action efficiencies, is the action efficiency of the target port node in the jth group of action efficiencies; Determine the real-time port operation environment level according to the real-time port environment data, and calculate the real-time action efficiency of each of the port nodes according to the real-time operation data; Recording the action efficiency data subset under the real-time port operation environment level as the target efficiency subset; In the target efficiency subset, the equipment operation scheme corresponding to a group of action efficiencies with the greatest similarity to the real-time action efficiency is used as a backup scheduling scheme; In the state influence coefficient set, normalizing the state influence coefficient subset corresponding to the target efficiency subset to obtain a normalized state influence coefficient subset; The difference between the actual operation time of the equipment in the backup scheduling scheme and the theoretical operation time of the current equipment is recorded as the equipment operation difference, and the port node with the largest equipment operation difference is recorded as the hub node; Adjusting the action efficiency of the hub node, and adjusting the action efficiency of the associated nodes of the hub node using a state update function according to the normalized state influence coefficient subset; Calculate the predicted operation time of each device according to the adjusted action efficiency of the hub node and its associated nodes; Calculate the sum of the differences between the predicted running time of each device and the theoretical running time of the current device, and record it as the running time error; The hub node is continuously selected and the action efficiency of the hub node and its associated nodes is adjusted until the set number of iterations is reached, and the equipment operation plan corresponding to the minimum operating time error is used as the port scheduling plan.

2. The method for generating a port scheduling scheme based on digitization according to claim 1 is characterized in that: The historical environmental data of the port include the historical temperature of the port, the historical humidity of the port, the historical wind speed of the port, the historical rainfall of the port and the historical hydrological data of the port. The historical hydrological data of the port include the historical wave height of the port and the historical water flow speed of the port. The historical operating data specifically include equipment operation data and cargo handling volume. The equipment operation data include the actual operation time of the equipment and the theoretical operation time of the equipment.

3. The method for generating a port scheduling scheme based on digitization according to claim 1 is characterized in that: The state update function satisfies the following relationship: in, Update the action efficiency value of the i-th associated node of the hub node, is the action efficiency of the i-th associated node of the hub node, is the normalized state influence coefficient of the hub node on the i-th associated node, is the efficiency of the hub node after adjustment. is the unregulated efficiency of the hub node's actions.

4. A digital port dispatching scheme generation system, characterized in that: The digital-based port scheduling scheme generation system comprises: a data acquisition device, a processor, a storage device and a data output device, wherein the storage device comprises a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and wherein the computer program comprises program instructions, and when the program instructions are executed by the processor, the processor implements the digital-based port scheduling scheme generation method as described in any one of claims 1 to 3.

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