Carbon sequestration transportation path optimization method based on mileage saving method and geographic information fusion

Abstract

The invention discloses a mileage saving method and geographic information fused carbon sequestration transportation path optimization method, and relates to the technical field of carbon sequestration and dual-carbon, and the mileage saving method and geographic information fused carbon sequestration transportation path optimization method mainly comprises the steps: obtaining a spherical distance matrix according to the coordinates of an emission source and a storage point; obtaining the saved mileage value between the emission sources according to the spherical distance matrix; constructing an initial path according to the saved mileage value between the emission sources; inserting an unaccessed emission source according to the initial path to carry out multi-path expansion to obtain an updated path; and calculating a path connection saving value according to the updated path, and performing fusion to obtain a fused path. According to the carbon sequestration transportation path optimization method integrating the mileage saving method and the geographic information, the path construction space rationality and the engineering applicability can be improved, the transportation efficiency is improved, and the transportation cost is reduced.

Description

Technical Field

[0001] This invention relates to the fields of carbon sequestration and dual-carbon technology, and more specifically, to a method for optimizing carbon sequestration transportation routes by integrating mileage-saving methods with geographic information. Background Technology

[0002] With the advancement of the "dual carbon" goals, carbon capture, utilization, and storage (CCUS) systems... Optimizing transportation routes has become a key aspect. The traditional Clarke-Wright Savings Algorithm is primarily used for constructing closed paths in Vehicle Routing Problems (VRP), but in the CCUS transportation scenario, Emission sources are typically widely distributed, and the transport routes are one-way open paths, requiring no return to the origin.

[0003] The existing technology has the following shortcomings: 1. Inadequate route construction: Most algorithms fail to consider the geographical distribution characteristics between cities; 2. Lack of consistent directional judgment: This can easily lead to ineffective detours such as "going south first and then north"; 3. Ignoring real-world road limitations: For example, some cities cannot be directly connected due to natural obstacles such as seas and mountains; 4. Does not support path fusion: Each path runs independently, resulting in duplicate trips and wasted resources; 5. Not applicable to CCUS scenarios: Most studies are still based on closed-loop paths, which does not conform to actual transportation logic.

[0004] Therefore, traditional route planning methods suffer from problems such as severe route detours, unreasonable route construction, and route duplication in CCUS scenarios. There is an urgent need to propose an open route optimization method suitable for carbon sequestration transportation networks, which can reduce total transportation costs while ensuring route rationality.

[0005] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The purpose of this invention is to provide a carbon sequestration transportation route optimization method that integrates the mileage-saving method and geographic information, which can improve the spatial rationality and engineering applicability of route construction, increase transportation efficiency, and reduce transportation costs.

[0007] This invention provides a carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information, comprising the following steps: S1: Obtain the spherical distance matrix based on the coordinates of the emission source and storage point; S2: Based on the spherical distance matrix, obtain the mileage saving value between emission sources; S3: Construct an initial path based on the mileage savings between the emission sources; S4: Based on the initial path, insert unvisited emission sources to perform multipath expansion and obtain an updated path; S5: Calculate the path connection saving value based on the updated path, and merge the paths based on the path connection saving value to obtain the merged path.

[0008] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the carbon sequestration transport route optimization method that integrates the mileage saving method and geographic information described above.

[0009] The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion provided by this invention has the following beneficial effects: This invention presents an open transport route planning method from multiple emission sources to a single storage point. It is a Path Network Optimization Method (PNOM) for carbon sequestration transport routes based on the mileage-saving method and geographic information fusion. Under the premise of the same open route construction, it further incorporates geographic information, using the Haversine formula to construct a spherical distance matrix to improve the spatial rationality of the route construction. The Clarke-Wright mileage-saving method is extended to the CCUS transport network optimization scenario, combining the principle of maximizing mileage savings for route construction, eliminating the need to return to the starting point. This invention proposes a route fusion mechanism, allowing multiple routes to be connected through shared city nodes, reducing redundant travel. This invention incorporates directional consistency judgment, evaluating changes in route direction when inserting cities to avoid ineffective detours, and supports real-world road network limitations, such as the inability to directly connect cities across sea areas or without land connections. It constructs one or more optimal transport routes, ensuring that all emission sources ultimately converge at the storage point, ensuring the completion of the transport task, and making the final generated transport routes more closely resemble the actual road network layout. This significantly improves the spatial rationality and engineering applicability of the route construction, increases transport efficiency, and reduces costs, making it suitable for various applications. It has good engineering applicability and prospects for promotion and application in the scenario of optimizing pipeline or highway transportation networks. Attached Figure Description

[0010] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart of the carbon sequestration transportation route optimization method that integrates the mileage saving method with geographic information provided by the present invention; Figure 2This is a schematic diagram of the carbon sequestration transportation route optimization method that integrates the mileage saving method and geographic information provided by the present invention. Detailed Implementation

[0011] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0012] Figure 1 A schematic diagram of the carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion, as shown in this embodiment, is illustrated. In this embodiment, the carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion includes the following steps: S1: Obtain the spherical distance matrix based on the coordinates of the emission source and the storage point; In one exemplary embodiment, step S1 specifically includes: obtaining a spherical distance matrix based on the coordinates of the emission source and the storage point, as shown in the formula: , , , , , in, For emission sources and emission sources The difference in latitude; and Sources of emissions and emission sources Latitude; For emission sources and emission sources Longitude difference; and respectively emission sources and emission sources Longitude; , as an intermediate variable, represents the sum of squares of the "semi-versus" function; The central angle (the angle between two points viewed from the Earth's center); For emission sources and emission sources The spherical distance between them, that is, the elements in the spherical distance matrix; The average radius of the Earth; S2: Based on the spherical distance matrix, obtain the mileage saving value between emission sources; In one exemplary embodiment, step S2 specifically includes: obtaining the mileage saving value between emission sources based on the spherical distance matrix, as shown in the formula: , in, For emission sources and emission sources Mileage savings between; For emission sources To the sealing point The distance; For emission sources To the sealing point The distance; S3: Construct an initial path based on the mileage savings between the emission sources; In one exemplary embodiment, step S3 specifically includes: constructing an initial path based on the mileage savings value between the emission sources, as shown in the formula: , , in, This indicates that the initial path segment is constructed by selecting the triplet with the largest mileage saving value from the emission sources closest to the storage point. Let represent the set of values ​​for the independent variable that maximize the objective function; Represents the set of candidate cities; Indicates the initial path; S4: Based on the initial path, insert unvisited emission sources to perform multipath expansion and obtain an updated path; In one exemplary embodiment, step S4 specifically includes: based on the initial path, inserting unvisited emission sources to perform multipath expansion, obtaining an updated path, as shown in the formula: , , , in, To update the path; Let represent the set of values ​​for the independent variable that minimize the objective function; Indicates the insertion of an unvisited emission source. Arrive at the location The new path length after that; For the current path The total distance; The first in the original path and The distance between cities; To insert unvisited emission sources Distance from the previous emission source; To insert unvisited emission sources Distance to the next emission source The current path; Indicates the last city visited (at the sealing point) Before); S5: Calculate the path connection saving value based on the updated path, and merge the paths based on the path connection saving value to obtain the merged path; In one exemplary embodiment, the calculated path connectivity savings value is as follows: , in, The path connection saves value, that is, the path and path The savings achieved by connecting through shared city nodes; Indicates the path and The total length of the new path after merging.

[0013] In one exemplary embodiment, the carbon sequestration transport route optimization method that integrates the mileage-saving method with geographic information further includes: imposing directional consistency constraints on the route, as shown in the formula: , , in, Represents the current path direction vector; This indicates the number of cities visited in the current path (excluding archive points); Indicates the first Geographic coordinate vectors (longitude, latitude) of each city; This indicates the angle of change of direction after inserting an unvisited emission source. If this angle of change is greater than a preset threshold, the insertion method will be rejected. This represents the direction vector of a newly inserted, unvisited emission source; In one exemplary embodiment, the preset threshold is: .

[0014] In one exemplary embodiment, the carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information further includes: excluding city pairs that cross sea areas or have no land connection from the route. As an exemplary embodiment, the city pair here refers to the node pair consisting of the cities where the emission source is located.

[0015] It should be noted that the above-mentioned emission sources are... The collection point and sealing point are the final destination for transportation.

[0016] In some embodiments, the carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information described above can also be implemented in the following ways.

[0017] like Figure 2 As shown, in this embodiment, the carbon sequestration transport route optimization method that integrates the mileage-saving method and geographic information includes the following steps: Collect data from multiple cities Geographic coordinates of the emission source; Construct the spherical distance matrix using the Haversine formula; Calculate the mileage savings between emission sources ; Construct an initial path segment and progressively insert unvisited emission sources; Supports multi-path construction and fusion mechanisms; Add a direction consistency judgment mechanism; Exclude cities that span sea areas or have no land connection; Output path network to ensure that all urban emission sources are ultimately accessible to the storage point.

[0018] Specifically, the aforementioned direction consistency judgment mechanism compares the path direction vector with the direction vector of the newly inserted city. If the angle is greater than a set threshold (e.g., ...), the mechanism determines the direction consistency. If the condition is met, then the insertion method will be rejected.

[0019] Specifically, the aforementioned path fusion mechanism selects the path combination that minimizes the total cost by comparing the changes in total travel distance before and after path merging.

[0020] It should be noted that the above methods are particularly applicable to open-path transportation scenarios such as carbon capture and storage (CCUS) transport network optimization, waste collection systems, and centralized express delivery.

[0021] In some embodiments, the carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information described above can also be implemented in the following ways.

[0022] In this embodiment, the carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information includes the following: (1) City coordinate acquisition Collect multiple The latitude and longitude information of the emission source cities is stored in a database.

[0023] (2) Calculation of distance between cities The Haversine formula is used to calculate the spherical straight-line distance between any two cities based on their latitude and longitude. The formula is as follows:

[0024]

[0025]

[0026]

[0027] in: , :City Latitude and longitude; :City and city The spherical distance between them; (3) Calculation of mileage savings Define two emission source cities Mileage savings between for:

[0028] in: :City To the sealing point The distance; :City To the sealing point The distance; :City With the city The spherical distance between them.

[0029] The higher the mileage saving value, the more distance is saved by merging the two cities into the same route.

[0030] (4) Initial path construction The initial path segment is constructed by selecting the triplet with the largest mileage saving value from the city closest to the storage point:

[0031] in: init :Collection of candidate cities; Construct the initial path:

[0032] (5) Multi-path expansion and insertion strategy For the current path Try to visit unvisited cities Insert at any position And update the path in the way that minimizes the total distance:

[0033] in, Current path P k Total distance; The first in the original path and The distance between cities; Insert city Distance from the previous city; Insert city Distance to the next city; Insert city Arrive at the location The new path length after that.

[0034] Ultimately, the optimal insertion method was selected:

[0035] (6) Path connection and fusion mechanism Multiple paths can be connected or merged by sharing city nodes, and the savings brought by path connection are defined as follows:

[0036] like This indicates that path segments can be merged.

[0037] (7) Consistency constraints between geographic information and direction A path direction consistency judgment mechanism is introduced to avoid invalid detours such as "going south first and then north":

[0038] Define the direction change angle after inserting a city:

[0039] If the angle is greater than the set threshold (e.g.) If the condition is met, then the insertion method will be rejected.

[0040] (8) Actual road network constraints Excluding routes that cannot be directly connected between certain cities (such as Macau) (Due to the sea barrier, direct connections between Shenzhen and Shenzhen are not possible)

[0041] Where: A: the set of all feasible path edges.

[0042] (9) Final path network output Output a transportation network structure consisting of several paths, ensuring that all emission source cities can reach the storage point via a certain path or its connecting paths, with the shortest total travel distance.

[0043] In some embodiments, the carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information described above can also be implemented in the following ways.

[0044] This embodiment uses a subset of city clusters as an example, designating Huizhou as a carbon sequestration site and the remaining cities as carbon sources. Detailed steps are as follows.

[0045] Input data: as shown in Table 1; Table 1: Coordinates of Emission Source Cities and Sequestration Sites

[0046] Step 1: Construct the spherical distance matrix (Haversine distance) The Haversine formula was used to calculate the spherical straight-line distances between all cities, which served as the basis for path construction, as shown in Table 2: Table 2: Distances between sample city pairs (unit: km)

[0047] Step 2: Calculate the mileage savings:

[0048] Using Huizhou as the endpoint, the mileage savings between each pair of cities are calculated, as shown in Table 3: Table 3: Example Mileage Savings (Unit: km)

[0049] After sorting, Zhongshan Foshan has the greatest savings and should be prioritized for merger.

[0050] Step 3: Construct the initial path segment Select the triplet with the largest mileage saving value from the city closest to the sealing point to construct the initial path segment.

[0051] The final initial path is: ; Total driving distance: ; (v) Step 4: Insert the remaining cities (Guangzhou, Qingyuan, Zhuhai, Macau, Shenzhen, Hong Kong) Insert unvisited cities into the current path one by one, and update the path in the way that minimizes the total distance.

[0052] The insertion order and strategy are as follows: Insert Guangzhou (number 0): You can try inserting it into ; Optimal insertion position: ; Added distance: ; Update path length: ; Insert Qingyuan (No. 4): Insert before Guangzhou: ; Added distance: ; Total distance: ; Insert Zhuhai (No. 8): Insert into ; Added distance: ; Total distance: ; Insert Macau (No. 7): Insert into ; Added distance: ; Total distance: ; Insert Shenzhen (number 1): Insert into Dongguan ← Shenzhen; Added distance: ; Total distance: ; Insert Hong Kong (No. 3): Insert into ; Added distance: ; Total distance: ; Step 5: Path Connection and Fusion Mechanism Detect cities where paths intersect and attempt to merge path segments to save total travel distance.

[0053] For example: “ "Already exists;" “ "Already exists; No additional connection required.

[0054] Step 6: Output the final path network structure, as shown in Table 4: Table 4: Path Network Structure

[0055] .

[0056] The method of the present invention will be compared with the traditional method in the following experiments; (I) Introduction to the Traditional Mileage-Saving Method The Clarke-Wright Savings Algorithm is a classic heuristic algorithm used to solve the Vehicle Routing Problem (VRP), particularly the closed-loop path planning problem involving multiple vehicles departing from and returning to a distribution center with capacity constraints. Proposed by Clarke and Wright in 1964, this method has been widely applied in logistics distribution, waste collection, and other fields.

[0057] To more fairly illustrate the advantages of this method, this embodiment improves the traditional mileage saving method into an open path, that is, removes the restriction of returning to the storage point, and only constructs a path from the emission source to the storage point, without forcing closure, so as to maintain the fairness of the comparison.

[0058] (ii) Comparison with similar cases Step 1: Initial route set (each city transported separately to the storage point) ,

[0059] The total distance is:

[0060] Step 2: Calculate the mileage savings:

[0061] For example: : ; : ; : ; After sorting, city pairs with higher savings values ​​will be merged first.

[0062] Step 3: Insert new city and update path Construct the initial path segment: ; Total distance: ; Insert Qingyuan: ; Added distance: ; Insert Zhuhai: ; Added distance: ; Insert Macau: ; Added distance: ; Insert Shenzhen: ; Added distance: ; Insert Hong Kong: ; Added distance: ; Step 4: The final traditional mileage-saving method (open path) is shown in Table 5: Table 5: Results of the Traditional Mileage Saving Method

[0063] ; However, please note that while Zhongshan, Foshan, Dongguan, and other border areas may be used multiple times, in reality, only one use is required.

[0064] Step 5: The total travel distance after path network optimization (traditional method) is shown in Table 6: Table 6: Total travel distance after path network optimization (traditional method)

[0065] ; Table 7 shows a comparative analysis of this method with the traditional mileage-saving method (open-ended) (under fair conditions): Table 7: Comparative Analysis of This Method and the Traditional Mileage Saving Method (Open-ended) (Under Fair Conditions)

[0066] Experiments show that in this case, the total travel distance of the route constructed by the traditional mileage-saving method is approximately 236 km, while that of this embodiment is only 205.83 km, saving approximately 13% of transportation costs. Furthermore, this embodiment reduces redundant travel through a route fusion mechanism and avoids invalid detours through direction consistency judgment, significantly improving the spatial rationality and engineering applicability of the route construction, demonstrating good engineering applicability and prospects for widespread application.

[0067] This embodiment provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information described above.

[0068] This embodiment provides a carbon sequestration transport route optimization system that integrates the mileage-saving method with geographic information, including the following core modules: Data acquisition module: used to obtain the geographical coordinates of the emission source cities, Basic data such as emissions and the specific location of the storage sites; Distance calculation module: Generates a spherical distance matrix between cities based on the Haversine formula, providing a spatial distance basis for subsequent path construction; The mileage saving calculation module further calculates the mileage saving values ​​between cities of different emission sources based on the generated distance matrix. , serving as an important reference indicator for path construction and optimization; Initial route construction module: Selects the triplet with the largest mileage saving value from all cities to construct the initial route, laying the foundation for the formation of the entire route network; Insertion strategy module: Based on the existing path, insert unvisited cities into appropriate positions in the current path according to the optimal insertion rules, thereby continuously expanding the path structure; Path fusion module: By analyzing the connection relationships between multiple paths, it determines whether path merging can be performed to reduce redundant trips and improve transportation efficiency; Directional consistency judgment module: When inserting a new city node, calculate and evaluate the change of the path's direction vector to avoid invalid detours and improve the spatial rationality of the path; Road restriction processing module: For city pairs that cannot be directly connected in reality (such as...) The system identifies and excludes routes to ensure that the generated routes conform to actual traffic conditions. Path output module: Finally outputs the complete path network structure, and can be combined with visualization tools to show the path direction, making it easier for users to understand and schedule execution.

[0069] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for optimizing carbon sequestration transport routes by integrating the mileage-saving method with geographic information, characterized in that, Includes the following steps: S1: Obtain the spherical distance matrix based on the coordinates of the emission source and storage point; S2: Based on the spherical distance matrix, obtain the mileage saving value between emission sources; S3: Construct an initial path based on the mileage savings between the emission sources; S4: Based on the initial path, insert unvisited emission sources to perform multipath expansion and obtain an updated path; S5: Calculate the path connection saving value based on the updated path, and merge the paths based on the path connection saving value to obtain the merged path.

2. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 1, characterized in that, Step S1 specifically includes: obtaining the spherical distance matrix based on the coordinates of the emission source and the storage point, as shown in the formula: ， ， ， ， ， in, For emission sources and emission sources The difference in latitude; and respectively emission sources and emission sources Latitude; For emission sources and emission sources Longitude difference; and respectively emission sources and emission sources Longitude; , as an intermediate variable, represents the sum of squares of the "semi-versus" function; The central angle; For emission sources and emission sources The spherical distance between them, that is, the elements in the spherical distance matrix; is the average radius of the Earth.

3. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 1, characterized in that, Step S2 specifically includes: obtaining the mileage saving value between emission sources based on the spherical distance matrix, as shown in the formula: ， in, For emission sources and emission sources Mileage savings between; For emission sources To the sealing point The distance; For emission sources To the sealing point The distance.

4. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 1, characterized in that, Step S3 specifically includes: constructing an initial path based on the mileage savings between the emission sources, as shown in the formula: ， ， in, This indicates that the initial path segment is constructed by selecting the triplet with the largest mileage saving value from the emission sources closest to the storage point. Let represent the set of values ​​for the independent variable that maximize the objective function; Represents the set of candidate cities; Indicates the initial path.

5. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 1, characterized in that, Step S4 specifically includes: based on the initial path, inserting unvisited emission sources to perform multipath expansion, obtaining an updated path, as shown in the formula: ， ， ， in, To update the path; Let represent the set of values ​​for the independent variable that minimize the objective function; Indicates the insertion of an unvisited emission source. Arrive at the location The new path length after that; For the current path The total distance; The first in the original path and The distance between cities; To insert unvisited emission sources Distance from the previous emission source; To insert unvisited emission sources Distance to the next emission source The current path; Indicates the last city visited.

6. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 1, characterized in that, The calculated path connection savings value is shown in the formula: ， in, The path connection saves value, that is, the path and path The savings achieved by connecting through shared city nodes; Indicates the path and The total length of the new path after merging.

7. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 1, characterized in that, The carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information also includes: imposing directional consistency constraints on the route, as shown in the formula: ， ， in, Represents the current path direction vector; This indicates the number of cities visited in the current path; Indicates the first Geographic coordinate vectors of each city; This indicates the angle of change of direction after inserting an unvisited emission source. If this angle of change is greater than a preset threshold, the insertion method will be rejected. This represents the direction vector of a newly inserted, unvisited emission source.

8. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 7, characterized in that, The preset threshold is .

9. The carbon sequestration transport route optimization method based on the mileage-saving method and geographic information fusion as described in claim 1, characterized in that, The carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information also includes excluding city pairs that cross sea areas or have no land connection from the route.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the carbon sequestration transport route optimization method that integrates the mileage saving method with geographic information as described in any one of claims 1-9.

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