Low-carbon scheduling method and system for logistics distribution centers based on real-time monitoring

Abstract

The present invention relates to the field of logistics distribution scheduling technology, and specifically to a low-carbon scheduling method and system for logistics distribution centers based on real-time monitoring, including: obtaining transit distribution nodes to construct a distribution network, obtaining the connected nodes of each transit distribution node; obtaining a real-time road speed sequence; analyzing the distribution of transit distribution nodes to obtain the isolation of each transit distribution node; analyzing the residence time to obtain the distribution load rate of each transit distribution node; obtaining the distribution route preference of each transit distribution node; obtaining the possibility of accidental carbon emissions based on road congestion; obtaining the low-carbon and high-efficiency priority of each transit distribution node during the current distribution; and utilizing the low-carbon and high-efficiency priority to achieve low-carbon scheduling optimization of logistics distribution. The present invention aims to consider the issue of carbon emissions between transit distribution nodes during the path planning of logistics distribution, so as to achieve the purpose of improving distribution scheduling efficiency while reducing carbon emissions.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics distribution scheduling, and in particular to a low-carbon scheduling method and system for a logistics distribution center based on real-time monitoring. Background Art

[0002] The logistics industry has long been a cornerstone supporting global economic development. Its core strengths lie in improving supply chain efficiency, reducing operating costs, and optimizing the customer experience. Existing logistics distribution models typically rely on direct delivery from a starting point to a destination. This involves delivering items from warehouses to transit nodes multiple times daily, and then transporting them through multiple transit nodes to their final destination. Existing technologies typically utilize ant colony algorithms to optimize the shortest path between the starting and ending points.

[0003] Although the shortest path scheduling model meets the logistics distribution efficiency, it does not take into account the actual road conditions of different transit and distribution nodes and the problem of object accumulation caused by simultaneous distribution. As a result, congested transit and distribution nodes and low-value transit and distribution nodes are used in the planning of the optimal path, which increases the carbon emission cost of logistics distribution and is not conducive to the establishment of a green and low-carbon logistics system. Summary of the Invention

[0004] The present invention provides a low-carbon scheduling method and system for a logistics distribution center based on real-time monitoring to solve existing problems.

[0005] The low-carbon scheduling method and system for logistics distribution centers based on real-time monitoring of the present invention adopt the following technical solutions:

[0006] One embodiment of the present invention provides a low-carbon scheduling method for a logistics distribution center based on real-time monitoring, the method comprising the following steps:

[0007] Based on historical delivery records, the locations of all transit delivery nodes, the retention time of all items in the transit delivery nodes, and the connectivity between the transit delivery nodes are obtained. A delivery network is constructed based on the locations and connectivity of all transit delivery nodes, and the connected nodes of each transit delivery node are obtained.

[0008] Obtain the actual road speed sequence of each transfer delivery node and its connected nodes during the current delivery;

[0009] Analyze the distribution of each transit and distribution node in the distribution network relative to its connected nodes to obtain the isolation of each transit and distribution node;

[0010] Analyze the retention time of all items in each transit and distribution node based on historical distribution records to obtain the distribution load rate of each transit and distribution node;

[0011] Combining the isolation and the delivery full load rate, obtaining the delivery route optimization degree of each transit delivery node;

[0012] Analyze the congestion situation of each transfer and delivery node and its connected nodes during the current delivery according to the road real-time speed sequence, and obtain the possibility of accidental carbon emissions of each transfer and delivery node during the current delivery;

[0013] Using the delivery route preference as a weight, the probability of accidental carbon emissions is weighted to obtain the low-carbon and high-efficiency priority of each transit delivery node during the current delivery;

[0014] The low-carbon and high-efficiency priorities are utilized to achieve low-carbon scheduling optimization of logistics distribution.

[0015] Preferably, the steps of obtaining the locations of all transit delivery nodes, the retention time of all objects in the transit delivery nodes, and the connectivity between the transit delivery nodes based on historical delivery records, constructing a delivery network based on the locations and connectivity of all transit delivery nodes, and obtaining the connected nodes of each transit delivery node include:

[0016] Obtaining the locations of all transit delivery nodes and their connectivity with other transit delivery nodes from the historical delivery records of the logistics distribution center, as well as the retention time of each item in each transit delivery node in the historical delivery records; the connectivity includes connectivity and non-connectivity;

[0017] Construct a regional graph based on the historical delivery records of the logistics distribution center; if the connectivity of two transit delivery nodes in the regional graph is connected, the distance between the two transit delivery nodes is recorded as the degree value of the two transit delivery nodes;

[0018] Taking all transit and delivery nodes as nodes of the topological network structure, the topological network structure constructed according to the degree of all nodes in the topological network structure and the connected transit and delivery nodes is recorded as the distribution network;

[0019] The other transit delivery nodes in the distribution network that are connected to each transit delivery node are recorded as the connected nodes of each transit delivery node.

[0020] Preferably, the step of obtaining the road speed sequence of each transit delivery node and its connected nodes during the current delivery includes:

[0021] The sequence consisting of the speed per minute of the delivery vehicle on the path from each transit delivery node to each of its connected nodes during the most recent delivery before the current delivery is recorded as the actual road speed sequence of each transit delivery node and each of its connected nodes during the current delivery.

[0022] Preferably, the specific steps of obtaining the isolation of the transit and delivery node include:

[0023] The average value of the degree of each transit delivery node in the distribution network and all its connected nodes is recorded as the geographical independence of each transit delivery node;

[0024] The ratio of the geographical independence of each transit and distribution node to the average geographical independence of all transit and distribution nodes except this transit and distribution node is recorded as the relative independence degree of each transit and distribution node;

[0025] The ratio of the number of items passing through each transit delivery node in the historical delivery records to the average number of items passing through all transit delivery nodes is recorded as the delivery volume demand level of each transit delivery node;

[0026] The isolation of each transit and delivery node is obtained, wherein the isolation is in direct proportion to the relative independence degree, and in inverse proportion to the delivery volume demand degree.

[0027] Preferably, the specific steps of obtaining the delivery full load rate include:

[0028] Based on the historical delivery records, the detention time of all items in all transit delivery nodes is standardized to obtain the detention coefficient of each transit delivery node.

[0029] During the current delivery, obtain the average number of items in all transit delivery nodes and record it as the average retention quantity during the current delivery;

[0030] Obtaining a capacity priority of each transit delivery node during the current delivery, wherein the capacity priority is negatively correlated with a difference between the number of items in each transit delivery node during the current delivery and the average retention amount;

[0031] The delivery full load rate of each transit delivery node is obtained; the delivery full load rate is positively correlated with the retention coefficient and the capacity priority.

[0032] Preferably, the specific steps of obtaining the delivery route preference include:

[0033] The delivery distance preference of each transit delivery node is obtained, and the delivery distance preference is positively correlated with the isolation and the delivery full load rate.

[0034] Preferably, the specific steps of obtaining the possibility of accidental carbon emissions include:

[0035] During the current delivery, the mean of the road speed sequence between each transfer delivery node and each of its connected nodes is recorded as the efficient traffic degree of each transfer delivery node and each of its connected nodes; the standard deviation of the road speed sequence between each transfer delivery node and each of its connected nodes is recorded as the congestion coefficient of each transfer delivery node and each of its connected nodes;

[0036] Obtaining the road congestion level of each transit and delivery node during the current delivery based on the average of the efficient traffic levels of each transit and delivery node and each of its connected nodes, as well as the average of the congestion coefficients. The road congestion level is negatively correlated with the average of the efficient traffic levels and positively correlated with the average of the congestion coefficients.

[0037] During the current delivery, the difference between the road congestion level of each transit and delivery node and the mean of the road congestion levels of all transit and delivery nodes is normalized and recorded as the possibility of accidental carbon emissions of each transit and delivery node during the current delivery.

[0038] Preferably, the specific steps of obtaining the low-carbon and high-efficiency priority include:

[0039] The delivery distance preference of each transit and delivery node is used to perform positive correlation weighting on the possibility of accidental carbon emissions of each transit and delivery node during the current delivery, so as to obtain the low-carbon and high-efficiency priority of each transit and delivery node during the current delivery. The low-carbon and high-efficiency priority is negatively correlated with the possibility of accidental carbon emissions.

[0040] Preferably, the low-carbon scheduling optimization of logistics distribution achieved by utilizing the low-carbon and high-efficiency priority includes:

[0041] (1) Obtain the starting point and ending point of the current delivery in the distribution network as the starting point and ending point of the ant colony algorithm for path planning;

[0042] (2) Constructing an ant colony algorithm planning model: taking the degree between each transit delivery node and its connected nodes as the path to be planned between each transit delivery node and its connected nodes;

[0043] (3) The product of the degree value between each transit and distribution node and its connected nodes and the low-carbon and high-efficiency priority of each transit and distribution node is used as the graph structure weight of the path to be planned between each transit and distribution node and its connected nodes when the ant colony algorithm performs path planning;

[0044] (4) Initialize the pheromone matrix and initialize the pheromone on each degree in the distribution network;

[0045] (5) Initialize ant positions: Randomly select the initial positions of the initial ants in the distribution network;

[0046] (6) Use the ant colony algorithm to plan the path so that the sum of the graph structure weights between all the transfer and distribution nodes between the starting point and the end point of the path planning is minimized. The sequence of all the transfer and distribution nodes between the starting point and the end point that satisfies the minimum sum of the graph structure weights is recorded as the logistics distribution path for the current delivery.

[0047] The present invention also proposes a low-carbon scheduling system for logistics distribution centers based on real-time monitoring. The system includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0048] The beneficial effects of the technical solution of the present invention are as follows: the present invention obtains the positions of all transit distribution nodes, the detention time of all objects in the transit distribution nodes and the connectivity between the transit distribution nodes based on historical distribution records, constructs a distribution network based on the positions and connectivity of all transit distribution nodes, and obtains the connectivity nodes of each transit distribution node; obtains the road actual speed sequence of each transit distribution node and its connectivity nodes during the current distribution; analyzes the distribution of each transit distribution node relative to its connectivity nodes in the distribution network, and obtains the isolation of each transit distribution node; uses the isolation to reflect the distance of each transit distribution node in space compared with other transit distribution nodes, and then selects transit distribution nodes that are easy to reach when planning the distribution route; analyzes the detention time of all objects in each transit distribution node under the historical distribution records, and obtains the traffic speed sequence of each transit distribution node. The distribution load rate of the distribution node; by analyzing the detention time of the objects in each transit distribution node, to reflect the distribution load situation of the transit distribution node during each logistics distribution, and reduce the carbon emissions generated by empty vehicle transportation; comprehensively considering the isolation and the distribution load rate, obtain the distribution route preference of each transit distribution node; according to the actual road speed sequence, analyze the congestion situation of each transit distribution node and its connected nodes during the current distribution, and obtain the possibility of accidental carbon emissions of each transit distribution node during the current distribution; by analyzing the congestion of the road, reflect the carbon emissions generated by the vehicle during non-efficient transportation; using the distribution route preference as a weight, weight the possibility of accidental carbon emissions, and obtain the low-carbon and high-efficiency priority of each transit distribution node during the current distribution; using the low-carbon and high-efficiency priority to achieve low-carbon scheduling optimization of logistics distribution. The present invention aims to consider the problem of carbon emissions between transit distribution nodes during the path planning of logistics distribution, so as to achieve the purpose of improving distribution scheduling efficiency while reducing carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 This is a flowchart of the steps of the low-carbon scheduling method for logistics distribution centers based on real-time monitoring of the present invention. DETAILED DESCRIPTION

[0051] To further illustrate the technical means and effects of the present invention to achieve the intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effects of the low-carbon scheduling method and system for logistics distribution centers based on real-time monitoring proposed by the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable form.

[0052] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0053] The specific scheme of the low-carbon scheduling method and system for logistics distribution centers based on real-time monitoring provided by the present invention is described in detail below with reference to the accompanying drawings.

[0054] See also Figure 1 , which shows a flowchart of a low-carbon scheduling method for a logistics distribution center based on real-time monitoring provided by an embodiment of the present invention, the method includes the following steps:

[0055] Step S001: Obtain the locations of all transit and delivery nodes, the residence time of all items in the transit and delivery nodes, and the connectivity between the transit and delivery nodes based on historical delivery records. Build a delivery network based on the locations and connectivity of all transit and delivery nodes, and obtain the connected nodes of each transit and delivery node. Obtain the actual road speed sequence between each transit and delivery node and its connected nodes during the current delivery.

[0056] It should be noted that logistics distribution centers improve delivery efficiency by planning routes from the starting point to the end point for the items to be delivered. However, this process is affected by road congestion along the delivery route, the accumulation of items at the delivery nodes, and the delivery load factor, resulting in unnecessary carbon emissions during delivery and failing to meet the requirements of low-carbon delivery. Therefore, this embodiment takes low-carbon emission requirements into account through real-time monitoring data, thereby achieving low-carbon delivery scheduling. Therefore, it is first necessary to obtain the required real-time monitoring data and distribution network.

[0057] Preferably, the locations of all transit delivery nodes, the retention time of all objects in the transit delivery nodes, and the connectivity between the transit delivery nodes are obtained based on historical delivery records, and a delivery network is constructed based on the locations and connectivity of all transit delivery nodes. The specific steps for obtaining the connected nodes of each transit delivery node are as follows:

[0058] In the historical delivery records of the logistics distribution center, obtain the location of all transit delivery nodes and their connectivity with other transit delivery nodes, as well as the detention time of each item in each transit delivery node in the historical delivery records;

[0059] It should be noted that the transit distribution node is the transit storage center passed through by all sub-distributions in the historical distribution records of the logistics distribution center. The location of the transit distribution node is the geographical coordinates of the transit storage center. If there is a transportation record in the historical distribution records of two transit distribution nodes that does not pass through other transit distribution nodes and arrives directly, then the two transit distribution nodes are recorded as connected, otherwise the two transit distribution nodes are recorded as disconnected; among them, the detention time is the time interval from each object entering the transit distribution node to leaving the transit distribution node.

[0060] Furthermore, a regional map is constructed based on the historical delivery records of the logistics distribution center, wherein the regional map includes the geographical coordinates of all transit delivery nodes corresponding to the transit storage center;

[0061] In the regional graph, if the connectivity of two transit delivery nodes is connected, the distance between the two transit delivery nodes is recorded as the degree value of the two transit delivery nodes; similarly, the degree of all connected transit delivery nodes is obtained;

[0062] Taking all transit and delivery nodes as nodes of the topological network structure, the topological network structure constructed according to the degree of all nodes in the topological network structure and the connected transit and delivery nodes is recorded as the distribution network;

[0063] It should be noted that constructing a topological network structure based on nodes and the degrees between nodes is a well-known technique and will not be described in detail in this embodiment.

[0064] Furthermore, other transit delivery nodes that are connected to each transit delivery node in the distribution network are recorded as connected nodes of each transit delivery node.

[0065] Preferably, the specific steps of obtaining the road speed sequence of each transit delivery node and its connected nodes during the current delivery include:

[0066] It should be noted that the main carbon emissions in the logistics distribution process are emissions from transportation equipment, and the actual road speed sequence between each node seriously affects carbon emissions. Therefore, this embodiment needs to obtain the actual road speed sequence between each transit and distribution node and its connected nodes.

[0067] It should be further explained that, since multiple vehicles may be dispatched for delivery on the same day during the logistics delivery process, and the traffic environment changes slowly, this embodiment uses the transportation conditions of vehicles on each transit delivery node and its connected nodes during the previous delivery of the current delivery as the actual road speed sequence for the current delivery.

[0068] Specifically, the sequence consisting of the speed per minute of the delivery vehicle on the path from each transit delivery node to each of its connected nodes during the most recent delivery before the current delivery is recorded as the actual road speed sequence between each transit delivery node and each of its connected nodes during the current delivery.

[0069] Step S002: Analyze the distribution of each transit delivery node in the distribution network relative to its connected nodes to obtain the isolation of each transit delivery node; analyze the residence time of all items in each transit delivery node based on historical delivery records to obtain the delivery load rate of each transit delivery node; and obtain the delivery route preference of each transit delivery node by combining the isolation and the delivery load rate.

[0070] It should be noted that during the logistics dispatch process of the logistics distribution center, each transit and distribution node needs to make multiple deliveries per day. During this process, if the transit and distribution node is located in a relatively independent area in the distribution network, that is, it is far away from other transit and distribution nodes in the surrounding area, then when the objects are transferred and delivered through this transit and distribution node, the carbon emissions generated by the vehicle will be greater than those of other transit and distribution nodes that are closer. In addition, during logistics distribution, if it is not necessary, the transit and distribution nodes that are farther away will not be selected for transfer. Therefore, the delivery efficiency of these transit and distribution nodes is lower, and the corresponding efficiency-carbon emission ratio is lower. Therefore, this embodiment first analyzes the distribution of each transit and distribution node compared to its connected nodes to obtain the isolation of each transit and distribution node.

[0071] Preferably, the specific steps of analyzing the distribution of each transit and delivery node relative to its connected nodes in the delivery network to obtain the isolation of each transit and delivery node include:

[0072] It should be noted that the degree between the transit distribution nodes in the distribution network represents the geographical distance between the two transit distribution nodes. Therefore, the smaller the degree, the farther its geographical location is from its connected nodes. When the transit distribution node is selected for transit, its path is longer, which results in a greater amount of carbon emissions.

[0073] The average value of the degree of each transit delivery node in the distribution network and all its connected nodes is recorded as the geographical independence of each transit delivery node;

[0074] The isolation of each transit and delivery node is obtained based on the geographical independence of each transit and delivery node and the number of objects passing through the transit and delivery node in the historical delivery records.

[0075] Specifically, based on the geographical independence of each transit and delivery node and the number of items that passed through the transit and delivery node in historical delivery records, the specific method for obtaining the isolation of each transit and delivery node is as follows:

[0076] The ratio of the geographical independence of each transit and distribution node to the average geographical independence of all transit and distribution nodes except this transit and distribution node is recorded as the relative independence degree of each transit and distribution node;

[0077] The ratio of the number of items passing through each transit delivery node in the historical delivery records to the average number of items passing through all transit delivery nodes is recorded as the delivery volume demand level of each transit delivery node;

[0078] The isolation of each transit and delivery node is obtained, wherein the isolation is in direct proportion to the relative independence degree, and in inverse proportion to the delivery volume demand degree.

[0079] As an example, the ratio of the relative independence degree of each transit delivery node to the delivery volume demand degree is recorded as the isolation of each transit delivery node. It should be noted that if the delivery volume demand degree of a transit delivery node is 0, the isolation of the transit delivery node is recorded as 1.

[0080] It should be noted that the greater the relative independence, the longer the path length of the transit distribution node compared with other transit distribution nodes; the greater the distribution volume demand, the greater the distribution volume demand, which indicates that in the historical distribution records, even if the transit distribution node is geographically farther away from its connected nodes, the number of objects delivered to the transit distribution node is greater, that is, the transportation demand to reach other transit distribution nodes through the transit distribution node is greater. Therefore, the relative independence is weakened by using the distribution volume demand as a weakening weight to obtain the isolation of each transit distribution node.

[0081] It should be noted that, when transporting goods from any transit delivery node to its connected nodes in a distribution center, the carbon emissions generated are the same, ignoring the impact of road factors. However, when goods from the same transit delivery node need to be transported to its connected nodes, the more items the transit delivery node transports simultaneously, that is, the more fully loaded the vehicle is during this transport, the lower the average carbon emissions per item. Furthermore, the more items a transit delivery node holds and the longer they remain, the higher the full load factor of its distribution equipment, and the lower the average carbon emissions per item. Therefore, this embodiment analyzes the retention time of each item to obtain the full load factor of each transit delivery node.

[0082] Preferably, the specific steps of analyzing the retention time of all items in each transit delivery node under the historical delivery records and obtaining the delivery load rate of each transit delivery node include:

[0083] Based on the historical delivery records, the detention time of all items in all transit delivery nodes is standardized to obtain the detention coefficient of each transit delivery node.

[0084] During the current delivery, the number of items in each transit delivery node is analyzed relative to the number of items in other transit delivery nodes to obtain the capacity priority of each transit delivery node;

[0085] Specifically, as an example, the detention time of all items in all transit delivery nodes is used to standardize the detention time of all items in each transit delivery node under historical delivery records. The specific method to obtain the detention coefficient of each transit delivery node is as follows:

[0086] Under the historical delivery records, the ratio of the mean detention time of all items in each transit delivery node to the mean detention time of all items in all transit delivery nodes is recorded as the detention coefficient of each transit delivery node.

[0087] Furthermore, during the current delivery, the number of items in each transit delivery node is analyzed relative to the number of items in other transit delivery nodes, and the specific method for obtaining the capacity priority of each transit delivery node during the current delivery is as follows:

[0088] During the current delivery, the average number of items in all transfer delivery nodes is obtained and recorded as the average retention volume during the current delivery. The capacity priority of each transfer delivery node during the current delivery is obtained. The capacity priority is negatively correlated with the difference between the number of items in each transfer delivery node during the current delivery and the average retention volume. As an example, during the current delivery, The capacity priority of each transit and delivery node is calculated as follows:

[0089]

[0090] in, For the current delivery The capacity priority of the transit and delivery nodes, For the current delivery The number of items in the transit delivery nodes, is the average retention quantity during the current delivery, To take the absolute value function, is an exponential function with a natural constant as its base.

[0091] The delivery load rate of each transit delivery node is obtained; the delivery load rate is positively correlated with the retention coefficient and the capacity priority; as an example, in this embodiment, the product of the capacity priority of each transit delivery node and the retention coefficient of each transit delivery node during the current delivery is recorded as the delivery load rate of each transit delivery node.

[0092] It should be noted that after obtaining the isolation of each transit and distribution node and the delivery full load rate of each transit and distribution node, the delivery route preference of each transit and distribution node is obtained by comprehensively considering the isolation and delivery full load rate, which is used to reflect the transportation cost of each transit and distribution node compared with other transit and distribution nodes, as well as the accumulation of goods in each transit and distribution node and the full load situation during transportation.

[0093] Preferably, the specific method of obtaining the delivery route preference of each transit delivery node by combining the isolation and the delivery full load rate is as follows:

[0094] The delivery distance preference of each transit and delivery node is obtained, and the delivery distance preference is positively correlated with the isolation and the delivery load rate. As an example, in this embodiment, the product of the isolation of each transit and delivery node and the delivery load rate of each transit and delivery node is linearly normalized, and the result obtained is recorded as the delivery distance preference of each transit and delivery node.

[0095] Step S003: Analyze the congestion conditions of each transfer and delivery node and its connected nodes during the current delivery based on the actual road speed sequence to obtain the possibility of accidental carbon emissions of each transfer and delivery node during the current delivery; and use the delivery route preference as a weight to weight the possibility of accidental carbon emissions to obtain the low-carbon and high-efficiency priority of each transfer and delivery node during the current delivery.

[0096] It should be noted that existing logistics transportation mainly relies on automobile transportation, and the carbon emissions of automobiles are affected by the actual road conditions. When the vehicle is traveling at low speed, the gasoline in the internal combustion engine is not fully burned, and a large amount of hydrocarbons will be emitted, causing high carbon emissions and environmental pollution. Therefore, when the actual road conditions are better, that is, when there is no congestion from the transit and delivery node to its connected nodes, the unexpected carbon emissions generated during transportation from the transit and delivery node to its connected nodes will be greater; therefore, this embodiment obtains the possibility of unexpected carbon emissions from each transit and delivery node during the current delivery by analyzing the congestion reflected by the actual road speed sequence between each transit and delivery node and its connected nodes during the current delivery.

[0097] Preferably, the specific steps of analyzing the congestion situation of each transfer and delivery node and its connected nodes during the current delivery according to the road real-time speed sequence to obtain the possibility of accidental carbon emissions of each transfer and delivery node during the current delivery are:

[0098] Analyze the distribution of the road speed sequence of each transfer delivery node and each of its connected nodes during the current delivery, and obtain the road congestion level of each transfer delivery node during the current delivery;

[0099] According to the difference in road congestion levels between each transit and delivery node and other transit and delivery nodes during the current delivery, the possibility of accidental carbon emissions at each transit and delivery node during the current delivery is obtained.

[0100] Specifically, the distribution of the road speed sequence of each transfer delivery node and each of its connected nodes is analyzed during the current delivery, and the specific method for obtaining the road congestion level of each transfer delivery node during the current delivery is as follows:

[0101] It should be noted that when a vehicle maintains an efficient and stable driving mode, the fuel consumption is the most stable and the combustion efficiency is the highest, so the carbon emissions are the lowest. When the vehicle encounters traffic jams on the road and drives in a stop-and-go mode, it will produce additional carbon emissions compared to a stable driving mode. Therefore, this embodiment analyzes the distribution of the actual road speed sequence to obtain the road congestion level of each transit and delivery node during the current delivery.

[0102] During the current delivery, the mean of the road speed sequence between each transfer delivery node and each of its connected nodes is recorded as the efficient traffic degree of each transfer delivery node and each of its connected nodes; the standard deviation of the road speed sequence between each transfer delivery node and each of its connected nodes is recorded as the congestion coefficient of each transfer delivery node and each of its connected nodes;

[0103] According to the average value of the efficient traffic degree of each transit delivery node and each of its connected nodes, and the average value of the congestion coefficient, the road congestion degree of each transit delivery node during the current delivery is obtained. The road congestion degree is negatively correlated with the average value of the efficient traffic degree and positively correlated with the average value of the congestion coefficient. As an example, during the current delivery, The degree of road congestion at the transfer and delivery nodes The calculation method is:

[0104]

[0105] in, For the The transit and delivery node and its The efficient passage degree of connected nodes, For the A transit delivery node and its The congestion coefficient of the connected nodes; is a linear normalization function; To find the mean function.

[0106] Furthermore, based on the difference in road congestion between each transit and delivery node and other transit and delivery nodes during the current delivery, the specific method for obtaining the possibility of accidental carbon emissions at each transit and delivery node during the current delivery is as follows:

[0107] During the current delivery, the difference between the road congestion level of each transit and delivery node and the mean of the road congestion levels of all transit and delivery nodes is normalized and recorded as the possibility of accidental carbon emissions of each transit and delivery node during the current delivery.

[0108] It should be noted that this embodiment uses a linear normalization function to perform normalization of the above operations, wherein the linear normalization function in this embodiment takes a maximum and minimum value normalization function as an example.

[0109] It should be noted that after obtaining the delivery route preference of each transit and distribution node and the possibility of accidental carbon emissions of each transit and distribution node during the current delivery, a larger value of the delivery route preference indicates that the transit and distribution node has a higher priority when planning the path for logistics delivery, and the possibility of accidental carbon emissions indicates that the transit and distribution node generates greater additional carbon emissions when planning the path for logistics delivery. Therefore, this embodiment uses the delivery route preference as a weight to weight the possibility of accidental carbon emissions to obtain the low-carbon and high-efficiency priority of each transit and distribution node during the current delivery.

[0110] Specifically, the delivery distance preference of each transit delivery node is used to perform positive correlation weighting on the possibility of accidental carbon emissions of each transit delivery node during the current delivery, and the low-carbon and high-efficiency priority of each transit delivery node during the current delivery is obtained. The low-carbon and high-efficiency priority is negatively correlated with the possibility of accidental carbon emissions. As an example, during the current delivery, The calculation method for the low-carbon and high-efficiency priority of each transit and distribution node is:

[0111] The first The delivery route preference of the transit delivery node is recorded as ;

[0112] The current delivery time The possibility of accidental carbon emissions at the transit and delivery nodes is recorded as ;

[0113]

[0114] in, For the current delivery Prioritize low-carbon and high-efficiency transit and distribution nodes.

[0115] Step S004: Utilize the low-carbon and high-efficiency priority to achieve low-carbon scheduling optimization of logistics distribution.

[0116] It should be noted that the existing logistics distribution usually samples the ant colony algorithm to plan the shortest path when planning the path of the transit distribution nodes. This embodiment takes into account the carbon emissions during the transfer to each transit distribution node, thereby considering both the path and carbon emission factors, thereby achieving low-carbon scheduling optimization during logistics distribution.

[0117] The specific steps are as follows:

[0118] 1. Obtain the starting and ending points of the current delivery in the distribution network as the starting and ending points for the ant colony algorithm to plan the path;

[0119] 2. Construct an ant colony algorithm planning model: the degree between each transit and delivery node and its connected nodes is used as the path to be planned between each transit and delivery node and its connected nodes;

[0120] 3. The product of the degree value between each transit and distribution node and its connected nodes and the low-carbon and high-efficiency priority of each transit and distribution node is used as the graph structure weight of the path to be planned between each transit and distribution node and its connected nodes when the ant colony algorithm performs path planning;

[0121] 4. Initialize the pheromone matrix and initialize the pheromone on each degree in the distribution network. In this embodiment, the initialization amount of pheromone is described as 0.01;

[0122] 5. Initialize ant positions: Randomly select the initial positions of an initial number of ants in the distribution network; in this embodiment, the number of ants is 25 as an example;

[0123] 6. Use the ant colony algorithm to plan the path so that the sum of the graph structure weights between all the transfer and distribution nodes between the starting point and the end point of the path planning is minimized. The sequence of all the transfer and distribution nodes between the starting point and the end point that satisfies the minimum sum of the graph structure weights is recorded as the logistics distribution path for the current delivery.

[0124] At this point, the logistics distribution path for the current delivery is obtained, completing the low-carbon scheduling of the logistics distribution center based on real-time monitoring.

[0125] It should be noted that the The model only shows negative correlation and the output of the constraint model is in In the interval, As the input of this model, it can be replaced by other models with the same purpose in specific implementation. This embodiment is just based on The model is used as an example for description without any specific limitation.

[0126] Another embodiment of the present invention provides a low-carbon scheduling system for a logistics distribution center based on real-time monitoring. The system includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, steps S001 to S004 of the above method are implemented.

[0127] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A low-carbon scheduling method for logistics distribution centers based on real-time monitoring, characterized by: The method comprises the following steps: Based on historical delivery records, the locations of all transit delivery nodes, the retention time of all items in the transit delivery nodes, and the connectivity between the transit delivery nodes are obtained. A delivery network is constructed based on the locations and connectivity of all transit delivery nodes, and the connected nodes of each transit delivery node are obtained. Obtain the actual road speed sequence of each transfer delivery node and its connected nodes during the current delivery; Analyze the distribution of each transit and distribution node in the distribution network relative to its connected nodes to obtain the isolation of each transit and distribution node; Analyze the retention time of all items in each transit and distribution node based on historical distribution records to obtain the distribution load rate of each transit and distribution node; Combining the isolation and the delivery full load rate, obtaining the delivery route optimization degree of each transit delivery node; Analyze the congestion situation of each transfer and delivery node and its connected nodes during the current delivery according to the road real-time speed sequence, and obtain the possibility of accidental carbon emissions of each transfer and delivery node during the current delivery; Using the delivery route preference as a weight, the probability of accidental carbon emissions is weighted to obtain the low-carbon and high-efficiency priority of each transit delivery node during the current delivery; Utilize the low-carbon and high-efficiency priorities to achieve low-carbon scheduling optimization of logistics distribution; The specific steps for obtaining the isolation of the transit and delivery node include: The average value of the degree of each transit delivery node in the distribution network and all its connected nodes is recorded as the geographical independence of each transit delivery node; The ratio of the geographical independence of each transit and distribution node to the average geographical independence of all transit and distribution nodes except this transit and distribution node is recorded as the relative independence degree of each transit and distribution node; The ratio of the number of items passing through each transit delivery node in the historical delivery records to the average number of items passing through all transit delivery nodes is recorded as the delivery volume demand level of each transit delivery node; Obtaining the isolation of each transit delivery node, wherein the isolation is in direct proportion to the relative independence degree and in inverse proportion to the delivery volume demand degree; The specific steps for obtaining the delivery full load rate include: Based on the historical delivery records, the detention time of all items in all transit delivery nodes is standardized to obtain the detention coefficient of each transit delivery node. During the current delivery, obtain the average number of items in all transit delivery nodes and record it as the average retention quantity during the current delivery; Obtaining a capacity priority of each transit delivery node during the current delivery, wherein the capacity priority is negatively correlated with a difference between the number of items in each transit delivery node during the current delivery and the average retention amount; Obtaining a delivery full load rate of each transit delivery node; wherein the delivery full load rate is positively correlated with the retention coefficient and the capacity priority; The specific steps for obtaining the possibility of accidental carbon emissions include: During the current delivery, the mean of the road speed sequence between each transfer delivery node and each of its connected nodes is recorded as the efficient traffic degree of each transfer delivery node and each of its connected nodes; the standard deviation of the road speed sequence between each transfer delivery node and each of its connected nodes is recorded as the congestion coefficient of each transfer delivery node and each of its connected nodes; Obtaining the road congestion level of each transit and delivery node during the current delivery based on the average of the efficient traffic levels of each transit and delivery node and each of its connected nodes, as well as the average of the congestion coefficients. The road congestion level is negatively correlated with the average of the efficient traffic levels and positively correlated with the average of the congestion coefficients. During the current delivery, the difference between the road congestion level of each transit and delivery node and the mean of the road congestion levels of all transit and delivery nodes is normalized and recorded as the possibility of accidental carbon emissions of each transit and delivery node during the current delivery.

2. The low-carbon scheduling method for logistics distribution centers based on real-time monitoring according to claim 1 is characterized in that: The method of obtaining the locations of all transit delivery nodes, the retention time of all objects in the transit delivery nodes, and the connectivity between the transit delivery nodes based on historical delivery records, constructing a delivery network based on the locations and connectivity of all transit delivery nodes, and obtaining the connected nodes of each transit delivery node includes: Obtaining the locations of all transit delivery nodes and their connectivity with other transit delivery nodes from the historical delivery records of the logistics distribution center, as well as the retention time of each item in each transit delivery node in the historical delivery records; the connectivity includes connectivity and non-connectivity; Construct a regional graph based on the historical delivery records of the logistics distribution center; if the connectivity of two transit delivery nodes in the regional graph is connected, the distance between the two transit delivery nodes is recorded as the degree value of the two transit delivery nodes; Taking all transit and delivery nodes as nodes of the topological network structure, the topological network structure constructed according to the degree of all nodes in the topological network structure and the connected transit and delivery nodes is recorded as the distribution network; The other transit delivery nodes in the distribution network that are connected to each transit delivery node are recorded as the connected nodes of each transit delivery node.

3. The low-carbon scheduling method for logistics distribution centers based on real-time monitoring according to claim 1 is characterized in that: The method of obtaining the road speed sequence of each transfer delivery node and its connected nodes during the current delivery includes: The sequence consisting of the speed per minute of the delivery vehicle on the path from each transit delivery node to each of its connected nodes during the most recent delivery before the current delivery is recorded as the actual road speed sequence of each transit delivery node and each of its connected nodes during the current delivery.

4. The low-carbon scheduling method for logistics distribution centers based on real-time monitoring according to claim 1 is characterized in that: The specific steps for obtaining the delivery route preference include: The delivery distance preference of each transit delivery node is obtained, and the delivery distance preference is positively correlated with the isolation and the delivery full load rate.

5. The low-carbon scheduling method for logistics distribution centers based on real-time monitoring according to claim 1 is characterized in that: The specific steps for obtaining the low-carbon and high-efficiency priority include: The delivery distance preference of each transit and delivery node is used to perform positive correlation weighting on the possibility of accidental carbon emissions of each transit and delivery node during the current delivery, so as to obtain the low-carbon and high-efficiency priority of each transit and delivery node during the current delivery. The low-carbon and high-efficiency priority is negatively correlated with the possibility of accidental carbon emissions.

6. The low-carbon scheduling method for logistics distribution centers based on real-time monitoring according to claim 1 is characterized in that: The low-carbon scheduling optimization of logistics distribution achieved by utilizing the low-carbon and high-efficiency priority includes: (1) Obtain the starting point and ending point of the current delivery in the distribution network as the starting point and ending point of the ant colony algorithm for path planning; (2) Constructing an ant colony algorithm planning model: taking the degree between each transit delivery node and its connected nodes as the path to be planned between each transit delivery node and its connected nodes; (3) The product of the degree value between each transit and distribution node and its connected nodes and the low-carbon and high-efficiency priority of each transit and distribution node is used as the graph structure weight of the path to be planned between each transit and distribution node and its connected nodes when the ant colony algorithm performs path planning; (4) Initialize the pheromone matrix and initialize the pheromone on each degree in the distribution network; (5) Initialize ant positions: Randomly select the initial positions of the initial ants in the distribution network; (6) Use the ant colony algorithm to plan the path so that the sum of the graph structure weights between all the transfer and distribution nodes between the starting point and the end point of the path planning is minimized. The sequence of all the transfer and distribution nodes between the starting point and the end point that satisfies the minimum sum of the graph structure weights is recorded as the logistics distribution path for the current delivery.

7. A low-carbon scheduling system for logistics distribution centers based on real-time monitoring, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the low-carbon scheduling method for a logistics distribution center based on real-time monitoring as described in any one of claims 1 to 6 are implemented.

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