Carbon constraint logistics path planning method and system based on multimodal transport

Abstract

The invention discloses a carbon constraint logistics path planning method and system based on multimodal transportation, relates to the field of path planning, and is used for providing a logistics path planning solution which meets diversified requirements of modern logistics on transportation types and cargo types. The method comprises the following steps: acquiring cargo information, starting and ending point information and transportation preference information; excluding nodes and edges which do not meet cargo transportation requirements from a logistics network according to the cargo information to obtain a transportation network; respectively calculating the transportation time, the transportation cost and the carbon emission of each edge in the transportation network; and searching the transportation path with the minimum transportation cost from the transportation network. According to the method, the transportation time, the transportation cost and the carbon emission under different transportation modes are comprehensively considered, and the unit distance cost and the path weight are dynamically adjusted, so that the logistics path can be matched with the cargo transportation requirements and the transportation preference requirements, and the diversified requirements of modern logistics on transportation types and cargo types are met.

Description

Technical Field

[0001] The present invention relates to the technical field of route planning, and in particular to a carbon-constrained logistics route planning method and system based on multimodal transport. Background Art

[0002] In today's world, the impact of global climate change is becoming increasingly significant, and carbon emissions have become a focal point of international concern. As a vital pillar of economic operations, the logistics and transportation industry has seen its carbon emissions continue to grow as it continues to develop, becoming one of the primary sources of carbon emissions. This has not only caused immeasurable damage to the ecological environment, but has also exposed the industry to increasingly stringent environmental regulations, both internationally and domestically. In this context, reducing carbon emissions in the logistics and transportation process and achieving green, sustainable development have become critical issues that the industry urgently needs to address.

[0003] Currently, existing methods for transport route planning face significant limitations in setting optimization objectives. Most route planning methods prioritize minimizing time or cost as their primary optimization goals. However, this single-minded approach completely ignores the crucial factor of carbon emissions during transportation. Against the backdrop of global initiatives promoting sustainable development, route planning that focuses solely on time and cost without considering carbon emissions is clearly unable to adapt to the demands of emerging industry developments. This not only hinders the green transformation of the logistics and transportation industry but also potentially exposes companies to higher environmental costs and development pressures in the future.

[0004] With the rapid development of modern logistics, intermodal transport, owing to its ability to fully integrate multiple modes of transportation, such as road, rail, water, and air, has become an increasingly important trend in the logistics industry. However, traditional route planning systems have exposed numerous problems when dealing with intermodal transport. Different types of cargo, such as perishables, flammable and explosive goods, and general cargo, have distinct requirements for transportation conditions. Furthermore, various modes of transportation, such as road, rail, water, and air, each have their own advantages and disadvantages in terms of transportation cost, time, carbon emissions, and flexibility. However, traditional route planning systems lack the ability to comprehensively optimize multiple modes and cargo types. This makes it difficult to comprehensively and efficiently plan optimal routes in complex intermodal transport scenarios that not only meet cargo transportation requirements but also balance time, cost, and carbon emissions. Consequently, they are unable to meet the complex and ever-changing demands of modern logistics.

[0005] Chinese patent document with publication number CN118586815A proposes a logistics path calculation method, equipment and storage medium under multimodal transport mode, which focuses on comprehensive consideration of cost and timeliness and provides a set of logistics path calculation solutions. This method uses path sorting and the generation of pre-selected paths to improve the efficiency of logistics transportation. However, this method mainly focuses on cost and timeliness during the path calculation process, and relatively insufficient consideration is given to carbon emissions. At the same time, this method lacks the ability to comprehensively optimize different modes of transportation and types of goods, and fails to fully meet the complex and changing needs of modern logistics. Chinese patent document with publication number CN115619037A proposes a multimodal transport multi-objective decision-making research method for quantifying the impact of carbon emissions. It focuses on establishing a multimodal transport path decision-making model under uncertain conditions and emphasizes the quantitative analysis of the impact of carbon emission policies. However, this method mainly focuses on the construction of theoretical models, and the dynamic adjustment of path optimization and user preferences in practical applications is relatively insufficient, and there is a lack of comprehensive consideration of different types of goods. Chinese patent publication CN112330070A proposes a method for optimizing intermodal transport routes for refrigerated containers under carbon emission constraints. This method focuses on minimizing transportation, transshipment, and refrigeration costs under carbon emission constraints by establishing a target optimization model. However, this method primarily emphasizes cost optimization, insufficiently considering both transportation time and carbon emissions, and fails to fully address the specific needs of different cargo types. Summary of the Invention

[0006] The object of the present invention is to provide a carbon-constrained logistics path planning method and system based on multimodal transport to address all or part of the above-mentioned problems, so as to comprehensively consider transportation time, transportation cost and carbon emissions, and provide a logistics path planning solution that meets the diverse needs of modern logistics for transportation types and cargo types.

[0007] The technical solution adopted in the present invention is as follows: A carbon-constrained logistics path planning method based on multimodal transport, comprising: Obtain cargo information, origin and destination information, and transportation preference information; Eliminating nodes and edges that do not meet cargo transportation requirements from a logistics network based on the cargo information to obtain a transportation network; the logistics network supports at least one transportation mode; and the cargo transportation requirements match the cargo information; Calculate the transportation time, transportation cost and carbon emissions of each edge in the transportation network separately; A transport path with the minimum transport cost is searched from the transport network, wherein the transport cost is calculated based on the transport time, transport cost and carbon emission of the edges between the nodes passed from the starting node to the destination node, and the edge weights matching the transport preference information.

[0008] Furthermore, each node in the logistics network supports at least one mode of transportation; each edge supports at least one mode of transportation.

[0009] Furthermore, the cargo transportation requirements include one or more requirements for the total volume, total weight, unit volume, unit weight, insulation, protection and maintenance of the cargo.

[0010] Furthermore, nodes and edges that do not meet cargo transportation requirements are excluded from the logistics network based on the cargo information, including: Based on the cargo information, exclude nodes that do not meet any of the cargo total volume, total weight, unit volume, unit weight, insulation, protection, and maintenance requirements, as well as the edges connected to the nodes; In the remaining logistics network, edges that do not meet the maintenance requirements are excluded.

[0011] Furthermore, methods for calculating edge carbon emissions include: For road transport: , in, is the total carbon emissions, Carbon emissions during transportation, Carbon emissions from the insulation process; For rail transport: Electric trains: , in, is the carbon emissions per unit of freight volume driven by electricity, is the power consumption rate, is the grid emission factor; Fuel drives the train: , in, is the carbon emission per unit of freight volume driven by fuel, is the fuel consumption rate, is the diesel fuel emission factor; For air transport: , in, is the total carbon emissions from aviation transport, is the transport distance, is the weight of the cargo, is the emission factor per unit transport distance.

[0012] Furthermore, searching for a transportation path with the lowest transportation cost in the transportation network includes: Starting from the starting node, the next-hop node with the minimum overall transportation cost is selected one by one from the neighboring nodes that have an edge connection with the current node, and connected to form a transportation path with the minimum transportation cost; among which, the overall transportation cost is composed of the actual transportation cost from the starting node to the current node and the optimal path cost from the current node to the destination node.

[0013] Furthermore, the actual transportation cost from the starting node to the current node is obtained by summing the transportation costs of each edge traversed from the starting node to the current node; wherein the calculation method of the edge transportation cost is: , Where, For the transport cost, 、 、 are the weight coefficients of transportation time, transportation cost and carbon emissions that match the transportation preference information, is the actual travel time of the edge, is the maximum travel time of the edge; is the actual transportation cost, is the maximum transport cost of the edge; The actual carbon emissions are The maximum carbon emission for the edge; is a transit penalty factor that matches the transportation preference information.

[0014] Furthermore, the optimal path cost from the current node to the destination node is calculated by multiplying the distance from the current node to the destination node and the minimum cost per unit distance; wherein the minimum cost per unit distance is The calculation method is: , in, They represent the time cost per unit distance, the cost cost per unit distance, and the carbon emission cost per unit distance, respectively, and are the minimum values of all transportation modes that can be selected from the current node to the destination node.

[0015] Furthermore, before excluding nodes and edges that do not meet cargo transportation requirements from the logistics network based on the cargo information, the method further includes: selecting a vehicle type that meets cargo transportation requirements based on information indicating the cargo type in the cargo information; The number of vehicles that meet the cargo transportation requirements when different vehicle types are selected is calculated based on the information indicating the total weight, total volume, unit weight and unit volume of the cargo in the cargo information.

[0016] The present invention also provides a carbon-constrained logistics path planning system based on multimodal transport, which includes a processor and a storage medium, wherein the storage medium stores computer instructions. When the processor runs the computer instructions, it can execute the above-mentioned carbon-constrained logistics path planning method based on multimodal transport.

[0017] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This application optimizes logistics routes based on user-entered cargo information and, while meeting the user's transportation preferences, comprehensively considers transportation time, transportation costs, and carbon emissions under different transportation modes. By dynamically adjusting unit distance costs and path weights, logistics routes are aligned with cargo transportation requirements and transportation preferences, meeting the diverse needs of modern logistics for transportation types and cargo types. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will now be described by way of example with reference to the accompanying drawings, in which: Figure 1 This is an operational flow chart of an embodiment of the carbon-constrained logistics path planning method based on multimodal transport in this application.

[0019] Figure 2 This is a flowchart of searching for the minimum cost transportation path in another embodiment of the carbon-constrained logistics path planning method based on multimodal transport of the present application.

[0020] Figure 3 This is a structural diagram of an embodiment of the carbon-constrained logistics path planning system based on multimodal transport in this application. DETAILED DESCRIPTION

[0021] All features disclosed in this specification, or all steps in the disclosed methods or processes, except mutually exclusive features and / or steps, can be combined in any manner.

[0022] Any feature disclosed in this specification (including any appended claims and abstract), unless otherwise stated, may be replaced by other equivalent or similar features. In other words, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

[0023] In view of the fact that current route planning mostly considers a single planning method of cost or distance, and route planning under known multimodal transport modes also focuses on transportation cost and time, and rarely considers carbon emission constraints, and is difficult to meet the diversified needs of modern logistics, the embodiment of the present application proposes a carbon-constrained logistics route planning method and system based on multimodal transport, which aims to solve the problem that the current logistics route planning method is difficult to meet the needs of modern logistics due to the single consideration of factors.

[0024] like Figure 1 As shown, the carbon-constrained logistics path planning method based on multimodal transport proposed in the embodiment of the present application includes: S1. Obtain cargo information, origin and destination information, and transportation preference information.

[0025] Cargo information refers to the attribute information of the cargo to be transported, which may include: 1) Cargo type: such as general cargo, fragile goods, fresh produce, oversized cargo, dangerous goods, living things, etc. Different cargo types require different transport vehicles. For example, fresh produce requires cold chain transport vehicles that meet insulation requirements, dangerous goods require dangerous goods transport vehicles that meet protection requirements, and living things require transport vehicles that meet live transport (maintenance) requirements.

[0026] 2) Cargo information: such as cargo weight and volume. Cargo weight includes gross weight and unit weight, while cargo volume includes gross volume and unit volume. Gross weight and volume are used to determine the total number of transport vehicles, while unit weight and volume are used to determine the minimum load or minimum volume vehicle type.

[0027] The origin and destination information refers to the starting and ending locations of the goods. In the logistics network, it is used to determine the starting and destination nodes.

[0028] Transportation preference information indicates the user's preferred requirements for cargo transportation. Examples include minimum time, minimum cost, minimum carbon emissions, minimum price (the lowest price refers to the lowest combined cost of time, cost, and carbon emissions), and minimum transit times. Transportation preference information can be input separately from cargo information, meaning the user specifically enters this information. Alternatively, it can be automatically identified based on cargo information. For example, if the cargo is identified as fragile, the minimum transit times setting may be used; if the cargo is identified as fresh produce, the minimum time setting may be used; and if the cargo is identified as general cargo, the minimum price setting may be used.

[0029] S2. Match road transport vehicles based on cargo information.

[0030] As mentioned above, different cargo types and different cargo information require different vehicle types and vehicle quantities. In this step S2, the vehicle type and corresponding quantity required for road transportation are first calculated based on the cargo information.

[0031] In some optional implementations, step S2 includes: S21. Select a vehicle type that meets the cargo transportation requirements based on the cargo type information (i.e., cargo type) in the cargo information.

[0032] For fresh goods, vehicles with refrigeration functions must be selected; For dangerous goods, you must choose a vehicle that is allowed to transport dangerous goods; For live animals, a vehicle that supports live transport must be selected.

[0033] S22. Calculate the number of vehicles that meet the cargo transportation requirements when different vehicle types are selected based on the information indicating the total weight, total volume, unit weight, and unit volume of the cargo in the cargo information.

[0034] First, based on the unit weight and unit volume of the cargo, identify a vehicle type that meets both minimum weight and minimum volume requirements. For example, if the unit volume of the cargo exceeds the carrying capacity of a van, then eliminate vans. Similarly, if the unit weight of the cargo exceeds the carrying capacity of a pickup truck, then eliminate pickup trucks. Based on this, identify a vehicle type that meets both the unit weight and unit volume requirements. If the cargo is loose, meaning there are no minimum transport weight or volume requirements, this process is unnecessary. Alternatively, if the logistics network only supports one type of vehicle (usually a large truck, which is not subject to unit volume and weight restrictions), then there is no need to consider the vehicle type requirements for unit weight and unit volume.

[0035] Next, calculate the number of vehicles required based on the total weight and volume of the cargo. The number of vehicles required varies depending on the load capacity and capacity of different vehicle types. For each type of vehicle that can transport cargo, calculate the number of vehicles required based on the total weight and volume of the cargo. The calculation method is: , Where N represents the number of vehicles required for each vehicle type; W and V represent the total weight and total volume of the cargo, respectively; Respectively represent the maximum load and maximum capacity of each type of vehicle.

[0036] Through the above method, the calculation of the number of vehicles required for different vehicle types under the road transport mode is completed in step S2.

[0037] It should be noted that if the vehicle type and number of vehicles required for the road transport mode have been determined in step S1, for example, if the vehicle information (vehicle type and number of vehicles) has been obtained when obtaining cargo information or vehicle preference information, step S2 can be omitted.

[0038] S3. Eliminate nodes and edges that do not meet cargo transportation requirements from the logistics network based on cargo information to obtain a transportation network.

[0039] In this application, a logistics network supports at least one mode of transportation, such as one or more of road, rail, air, and water transport. A logistics network consists of all logistics nodes and the edges between them. A logistics node is a logistics center that supports at least one mode of transportation. For example, a node may support air, road, and rail transport, while another node may only support road transport. Logistics node information includes basic attributes such as node name, node type (which may indicate supported modes of transportation), and node location (geographic location or city). It also includes functional attributes such as weight limits, volume limits, lifting equipment, cold chain support capabilities, hazardous materials handling capabilities, and live animal feeding capabilities. The functional attribute information includes weight limits, which record the maximum cargo weight supported by the node; volume limits, which record the maximum cargo volume supported by the node; lifting equipment, which records whether the node has loading and unloading or hoisting equipment; cold chain support capabilities, which record whether the node supports cold chain transportation; hazardous materials handling capabilities, which record whether the node supports hazardous materials transportation; and live animal feeding capabilities, which record whether the node has the conditions for feeding live animals. Based on the functional attribute information of a node, its support for cargo transportation requirements can be determined. The edges between nodes represent the transportation routes between logistics centers. Each edge supports at least one mode of transportation. Different modes of transportation can be labeled with corresponding edge information, or the edge information for different modes of transportation can be labeled on the same edge. Edge information includes the starting point name, end point name, path distance, transportation mode, transportation time, basic transportation cost, etc. Basic transportation cost refers to the cost that remains unchanged under different transportation modes. For example, for road transportation, it is the toll charged for that section of the route. The transportation cost is determined by the type and number of vehicles and is a variable. For rail, air, or water transportation, the basic transportation cost is the cost per unit quantity, such as the cost per ton of goods, the cost per cubic meter of goods, or the maximum cost per ton / cubic meter.

[0040] Cargo transportation requirements match cargo information. Different cargoes have different cargo transportation requirements. Different cargo transportation requirements may prevent some nodes or edges in the logistics network from being considered as candidate nodes or edges. As an optional implementation, nodes and edges that do not meet cargo transportation requirements are excluded from the logistics network based on cargo information, including: S31. Based on the cargo information, exclude nodes that do not meet any of the cargo total volume, total weight, unit volume, unit weight, insulation, protection, and maintenance requirements, as well as the edges connected to the nodes.

[0041] For example, for fresh produce, nodes without cold chain support capabilities need to be excluded; for live goods, nodes without live animal feeding capabilities need to be excluded; and for hazardous goods, nodes without hazardous material handling capabilities need to be excluded. Furthermore, for cargo with a certain total volume / unit volume or total weight / unit weight, nodes without lifting equipment may also need to be excluded. Generally speaking, cargo transportation requirements include one or more of the following: total volume, total weight, unit volume, unit weight, insulation, protection (e.g., hazardous material protection), and maintenance (e.g., live animal feeding).

[0042] Since nodes are not selectable, the edges between nodes must also be not selectable, so the edges connected to the excluded nodes also need to be excluded.

[0043] S32. In the remaining logistics network, exclude the edges that do not meet the maintenance requirements.

[0044] For live animal cargo, since live animals also have feeding interval requirements, we also need to exclude edges whose transportation time exceeds the feeding interval. For example, if two nodes both have live animal feeding capabilities and support both road and rail transportation, the road transportation time is 8 hours and the rail transportation time is 5 hours, but the required feeding interval is 6 hours, then road transportation is not feasible. Therefore, we need to exclude the corresponding edges and retain only the rail transportation method that meets the requirements.

[0045] By excluding non-selectable nodes and edges from the logistics network, a transportation network that supports the transportation of the current goods is obtained, and the nodes and edges in this transportation network all meet the transportation requirements for the goods. These alternative nodes and edges differ in distance, cost, and transportation mode. The alternative paths composed of different nodes and edges have different transportation times, transportation costs, and carbon emissions. This application also requires selecting the optimal path that matches the transportation preference information from these optional alternative paths, so as to obtain the lowest-cost transportation path while comprehensively considering transportation time, transportation cost, carbon emissions, and transportation preference information.

[0046] S4. Calculate the transportation time, transportation cost and carbon emissions of each edge in the transportation network respectively.

[0047] If the transport time of the edge is already marked in the logistics network, then there is no need to calculate the transport time of the edge separately in this step S4. Conversely, if the transport time of the edge is not marked in the logistics network, it is necessary to calculate the transport time based on the transport speed of different transportation modes and the transport distance of the edge.

[0048] The transportation cost is calculated based on the total weight and volume of the goods: For road transport, the type and number of vehicles required for transportation have been determined. By adding the transportation distance, tolls (single vehicle), unit transportation cost, etc., the transportation cost of road transport can be calculated.

[0049] In some optional implementations, the transportation cost of road transportation is calculated as follows: , in, It represents the transportation cost of road transportation; To represents the toll of a single vehicle; represents the transportation cost per unit distance of a single vehicle (excluding tolls); D represents the transportation distance; It indicates the amount by which actual carbon emissions exceed the carbon quota, which is obtained by subtracting the total carbon emissions from the carbon quota; Pr represents the carbon trading price.

[0050] The transportation costs of rail, air and water transport are calculated by dividing the total weight / total volume of the goods by the corresponding unit cost, and then adding the cost of the amount by which the actual carbon emissions exceed the carbon quota.

[0051] For carbon emissions, the calculation method varies depending on the mode of transportation.

[0052] 1) For road transport: , in, is the total carbon emissions, Carbon emissions during transportation, Carbon emissions during the insulation process.

[0053] The calculation method is: , Where, is the fuel emission factor , gasoline is 2.31 , diesel is 2.68 ; Actual fuel consumption rate , covering all means of transport (such as all vehicles).

[0054] The calculation method is: , Where, Fuel consumption rate when the vehicle is idling , Fuel consumption rate when the vehicle is fully loaded , is the vehicle's full load (tons), The maximum load capacity of the vehicle (tons).

[0055] The calculation method is: , Where, is the fuel consumption rate of the refrigeration equipment per unit time , covering all means of transport.

[0056] According to the calculated actual total carbon emissions , the difference between actual carbon emissions and carbon quotas can be calculated: , Where Q is the carbon quota, which is the maximum carbon emission allowed for free. , The difference between actual carbon emissions and (i.e., excess) carbon quota , when calculating the cost of carbon emissions, there are: .

[0057] 2) For rail transport: There are two driving modes for railway transportation: electric drive and fuel drive.

[0058] Electric trains: , in, is the carbon emissions per unit of freight transport under electric drive ( ton-kilometer), is the power consumption rate ( 1,000 tons per kilometer), is the grid emission factor ( ), usually takes a value of 0.5 . The value of depends on the train speed. , =4.5( 1,000 tons per kilometer); when the speed is between, =5.5( 1,000 tons per kilometer); when the speed , =7.0( Thousand tons per kilometer) Fuel drives the train: , in, Carbon emissions per unit of freight volume driven by fuel , Emission factor for diesel fuel , usually takes a value of 2.68 Fuel consumption rate The value of depends on the train speed. , When the speed is between, When the speed , .

[0059] 3) For air transport: , in, Total carbon emissions from air transport , is the transport distance (km), is the emission factor per unit transport distance . The value of is determined by the transport distance. When the distance is less than 1500 kilometers, ; When the distance is between 1500 and 4000 kilometers, ; When the distance is greater than 4000 kilometers, .

[0060] 4) For water transport, the calculation method is the same as that for air transport, except that the emission factor per unit transport distance is different.

[0061] S5. Search for the transportation path with the minimum transportation cost from the transportation network.

[0062] The transportation cost is calculated based on the transportation time, transportation cost, and carbon emissions of the edges between the nodes passed from the starting node to the destination node, as well as the edge weights matched to the transportation preference information. Since transportation time, transportation cost, and carbon emissions are comprehensively considered in the embodiments of the present application, the above-mentioned edge weights include weight coefficients of transportation time, transportation cost, and carbon emissions.

[0063] The transportation cost is calculated based on the transportation time, transportation cost and carbon emissions of the transportation route, as well as the total cost of these three aspects converted according to their importance (measured by the weight coefficient).

[0064] In some optional implementations, the method of searching for a transportation path with the lowest transportation cost in a transportation network includes: Starting from the starting node, the next hop node with the lowest overall transportation cost is selected one by one from the neighboring nodes that have an edge connection with the current node, and the transportation path with the lowest transportation cost is connected. The overall transportation cost is composed of the actual transportation cost from the starting node to the current node and the optimal path cost from the current node to the destination node. In other words, the overall transportation cost of the selected path includes the actual transportation cost from the starting node to the current node and the optimal path cost from the current node to the destination node. Let n represent the current node, Represents the overall transportation cost at the current node, which consists of two parts, namely the actual transportation cost from the starting node to the current node , and the optimal path cost from the current node to the destination node ,Right now: .

[0065] S51. Calculate the actual transportation cost from the starting node to the current node .

[0066] The actual transportation cost from the starting node to the current node is obtained by summing the transportation costs of each edge from the starting node to the current node.

[0067] The nodes and edges (transportation methods) passed through from the starting node to the current node have been determined. Therefore, the actual transportation cost from the starting node to the current node can be obtained by summing up the transportation cost of each edge that has been determined.

[0068] , i refers to the edge passed through, is the edge transportation cost, which represents the accumulation of the edge transportation costs of the edges passed.

[0069] In some optional implementations, the edge transport cost of the edge that has been experienced is calculated as follows: , Where, 、 、 The weight coefficients of transportation time, transportation cost and carbon emission are matched with the transportation preference information respectively. The corresponding weight coefficient is selected from the set weight coefficient group in advance according to the transportation preference information. For example, if the transportation preference information is the minimum transportation time, then select The highest set of weight coefficients. Similarly, if the transportation preference information is the lowest transportation cost, then choose The highest set of weight coefficients. is the actual travel time of the edge, that is, the transportation time corresponding to the selected transportation mode, The maximum travel time of the edge, that is, the maximum transportation time among all the transportation modes that can be selected between the nodes at both ends of the edge; is the actual transportation cost, The maximum transportation cost of the edge, that is, the maximum transportation cost among all the transportation modes that can be selected between the nodes at both ends of the edge; The actual carbon emissions are is the maximum carbon emission of the edge, that is, the maximum carbon emission of all available transportation modes between the nodes at both ends of the edge; The transit penalty factor is introduced to match the transportation preference information. It is intended to reduce the additional risks of special goods such as fragile items during transportation, encourage the selection of safer and more direct transportation routes, and reduce the number of transits. The P value is set in advance when determining the transportation preference information. The fewer the number of transits required, the larger the P value, so that the transportation cost calculated for the route with more transits is greater.

[0070] S52: Calculate the optimal path cost from the current node to the destination node.

[0071] The optimal path cost from the current node to the destination node is calculated by multiplying the distance from the current node to the destination node and the minimum cost per unit distance.

[0072] In some optional embodiments, the minimum cost per unit distance The calculation method is: , in, They represent the time cost per unit distance, the cost cost per unit distance, and the carbon emission cost per unit distance, respectively, and are the minimum values of all transportation modes that can be selected from the current node to the destination node.

[0073] For example, for a possible path from the current node to the destination node, the sum of the time taken for each edge (different transportation modes for the same path will have different total times) divided by the maximum time taken for that path (the sum of the transportation times for all edges with the longest transportation times) yields the time cost for each transportation mode on that path. Dividing the time cost for each transportation mode on that path by the total path length yields the time cost per unit distance for each mode. The minimum time cost per unit distance for each mode on that path is then selected to determine the total time cost per unit distance for that path. The same method is used to calculate the cost per unit distance and the carbon emission cost per unit distance.

[0074] Then, the smallest unit distance time cost, unit distance cost cost, and unit distance carbon emission cost of all optional paths from the current node to the destination node are selected to obtain .

[0075] On this basis, the weight coefficient set according to the transportation preference information , , , corresponding to Multiply them together and take the minimum of the three weighted costs as the minimum cost per unit distance The process of weighting the unit cost with a weight coefficient introduces the influence of transportation preference information on the optimization of the optimal path. While comprehensively considering transportation time, transportation cost and carbon emissions, transportation preference information is also given priority consideration, so that the optimized path meets the diverse needs of modern logistics for cargo transportation.

[0076] Determine the minimum cost per unit distance Based on this, we can get the optimal path cost from the current node to the destination node. : , Where, Indicates the Euclidean distance from the current node n to the destination node g.

[0077] Starting from the starting node, by continuously expanding the optional neighbor nodes, the neighbor node that minimizes the overall transportation cost is selected from the neighbor nodes expanded at each step as the next hop node, and this cycle is repeated until it is expanded to the destination node, and the transportation path with the minimum transportation cost that matches the transportation preference information is obtained.

[0078] In some other optional embodiments, the carbon-constrained logistics path planning method based on multimodal transport of the present application may not exclude edges that do not meet the maintenance requirements from the logistics network in step S2, but only exclude nodes that do not meet the cargo transportation requirements and the edges directly connected to the nodes. When expanding the nodes, it is determined whether the edges to the expanded nodes meet the maintenance requirements. If not, the expanded nodes are reselected, such as Figure 2 The rest of the process is the same as that of the above embodiments.

[0079] According to the idea of this application, Figure 3 As shown, embodiments of the present application also provide a carbon-constrained logistics routing planning system based on multimodal transport, which includes a processor and a storage medium. The storage medium stores computer instructions. When the processor executes the computer instructions, it can execute the carbon-constrained logistics routing planning method based on multimodal transport described in the above embodiment. The system enables communication between internal and external facilities through interface circuits, such as computer instructions transmitted between the processor and the storage medium, or the processor receives cargo information, origin and destination information, and transportation preference information from external facilities.

[0080] The present invention is not limited to the aforementioned specific embodiments, but extends to any new features or any new combination disclosed in this specification, as well as any new method or process steps or any new combination disclosed.

Claims

1. A carbon-constrained logistics path planning method based on multimodal transport, characterized in that: include: Obtain cargo information, origin and destination information, and transportation preference information; Eliminating nodes and edges that do not meet cargo transportation requirements from the logistics network based on the cargo information to obtain a transportation network; The logistics network supports at least one mode of transportation; the cargo transportation requirements match the cargo information; Calculate the transportation time, transportation cost and carbon emissions of each edge in the transportation network separately; A transport path with the minimum transport cost is searched from the transport network, wherein the transport cost is calculated based on the transport time, transport cost and carbon emission of the edges between the nodes passed from the starting node to the destination node, and the edge weights matching the transport preference information.

2. The carbon-constrained logistics path planning method based on multimodal transport according to claim 1, characterized in that: Each node in the logistics network supports at least one mode of transportation; each edge supports at least one mode of transportation.

3. The carbon-constrained logistics path planning method based on multimodal transport according to claim 2, characterized in that: The cargo transportation requirements include one or more requirements for the total volume, total weight, unit volume, unit weight, insulation, protection and maintenance of the cargo.

4. The carbon-constrained logistics path planning method based on multimodal transport according to claim 3, characterized in that: Nodes and edges that do not meet cargo transportation requirements are excluded from the logistics network based on the cargo information, including: Based on the cargo information, exclude nodes that do not meet any of the cargo total volume, total weight, unit volume, unit weight, insulation, protection, and maintenance requirements, as well as the edges connected to the nodes; In the remaining logistics network, edges that do not meet the maintenance requirements are excluded.

5. The carbon-constrained logistics path planning method based on multimodal transport according to claim 2, characterized in that: Methods for calculating marginal carbon emissions include: For road transport: ， in, is the total carbon emissions, Carbon emissions during transportation, Carbon emissions from the insulation process; For rail transport: Electric trains: , in, is the carbon emissions per unit of freight volume driven by electricity, is the power consumption rate, is the grid emission factor; Fuel drives the train: , in, is the carbon emission per unit of freight volume driven by fuel, is the fuel consumption rate, is the diesel fuel emission factor; For air transport: ， in, is the total carbon emissions from aviation transport, is the transport distance, is the weight of the cargo, is the emission factor per unit transport distance.

6. The carbon-constrained logistics path planning method based on multimodal transport according to any one of claims 2 to 5, characterized in that: Searching for a transportation path with the minimum transportation cost from the transportation network includes: Starting from the starting node, the next-hop node with the minimum overall transportation cost is selected one by one from the neighboring nodes that have an edge connection with the current node, and connected to form a transportation path with the minimum transportation cost; among which, the overall transportation cost is composed of the actual transportation cost from the starting node to the current node and the optimal path cost from the current node to the destination node.

7. The carbon-constrained logistics path planning method based on multimodal transport according to claim 6, characterized in that: The actual transportation cost from the starting node to the current node is obtained by summing the transportation costs of each edge from the starting node to the current node. The calculation method of the edge transportation cost is: ， Where, For the transport cost, 、 、 are the weight coefficients of transportation time, transportation cost and carbon emissions that match the transportation preference information, is the actual travel time of the edge, is the maximum travel time of the edge; is the actual transportation cost, is the maximum transport cost of the edge; The actual carbon emissions are The maximum carbon emission for the edge; is a transit penalty factor that matches the transportation preference information.

8. The carbon-constrained logistics path planning method based on multimodal transport according to claim 7, characterized in that: The optimal path cost from the current node to the destination node is calculated by multiplying the distance from the current node to the destination node and the minimum cost per unit distance; wherein, the minimum cost per unit distance is The calculation method is: ， in, They represent the time cost per unit distance, the cost cost per unit distance, and the carbon emission cost per unit distance, respectively, and are the minimum values of all transportation modes that can be selected from the current node to the destination node.

9. The carbon-constrained logistics path planning method based on multimodal transport according to claim 1, characterized in that: Before excluding nodes and edges that do not meet cargo transportation requirements from the logistics network based on the cargo information, the method further includes: selecting a vehicle type that meets cargo transportation requirements based on information indicating the cargo type in the cargo information; The number of vehicles that meet the cargo transportation requirements when different vehicle types are selected is calculated based on the information indicating the total weight, total volume, unit weight and unit volume of the cargo in the cargo information.

10. A carbon-constrained logistics path planning system based on multimodal transport, characterized in that: The method comprises a processor and a storage medium, wherein the storage medium stores computer instructions. When the processor runs the computer instructions, the method can execute the carbon-constrained logistics path planning method based on multimodal transport as described in any one of claims 1 to 9.

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