Logistics path scheduling method and system for logistics vehicle

Abstract

The invention discloses a logistics path scheduling method and system of a logistics vehicle, and relates to the technical field of path scheduling, carbon emission and energy consumption of a path are accurately calculated and screened through a high-precision map system and a graph search algorithm, and environmental friendliness is directly used as a key constraint condition of path selection; according to the method, the carbon emission and the oil consumption are definitely introduced as path evaluation indexes, and an environment-friendly coefficient is set, so that the selected path can reduce the carbon emission to the maximum extent; secondly, a multi-dimensional comprehensive cost evaluation model including load balance, road condition adaptability, vehicle long-term cost and the like is established, and energy consumption of logistics vehicles is effectively reduced by accurately calculating energy consumption loss under different paths; and the energy use efficiency can be scientifically quantified and optimized, so that the energy waste is reduced from the source, and the purposes of energy conservation and emission reduction are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of route scheduling, and in particular to a logistics route scheduling method and system for logistics vehicles. Background Art

[0002] With the rapid development of e-commerce and retail industries, the demand for logistics and transportation has increased significantly. However, the existing logistics vehicle routing scheduling methods are generally inefficient and fail to make full use of modern information technology for scientific optimization. This not only leads to a high vehicle idle rate and unreasonable route planning during transportation, but also brings a lot of energy waste and high carbon emissions.

[0003] Most of the current logistics routing scheduling methods are based on experience or simple routing algorithms, which fail to comprehensively consider factors such as vehicle load, road conditions, time constraints, and environmental impacts. This extensive routing scheduling model leads to the following problems: 1. Excessive energy consumption: Due to the failure to accurately optimize the route, vehicles often travel longer distances or get stuck in traffic jams, increasing fuel consumption; 2. Serious carbon emissions: The logistics industry is one of the main sources of greenhouse gas emissions. Traditional scheduling methods do not take carbon emission indicators as optimization targets, making it difficult to achieve environmentally friendly transportation; 3. Insufficient economic benefits: High vehicle maintenance costs, low road resource utilization and lack of transportation efficiency have all affected the company's operating profits.

[0004] Therefore, how to optimize the transportation efficiency of logistics vehicles, reduce energy consumption, and reduce carbon emissions through scientific route planning and scheduling methods has become a technical problem that the industry urgently needs to solve. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a logistics path scheduling method and system for logistics vehicles, which solves the problems in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A logistics path scheduling method for logistics vehicles, comprising: Step 1: Determine the departure and destination of the logistics vehicle, use the high-precision map system to optimize the logistics path process, model the logistics network as a weighted graph, generate a path set through a graph search algorithm, select a set of alternate paths that meet the constraints based on the total path length, total path time, and environmental friendliness, and sort them through a preset priority function to finally select the optimal set of alternate paths; Step 2: Obtain the optimal set of available alternative paths and determine the total cost of each available alternative path in the set of available alternative paths for logistics vehicle transportation; Step 3: According to the total cost of each available backup path in the available backup path set, a comprehensive priority evaluation is performed on each available backup path to obtain a comprehensive priority evaluation coefficient of each available backup path, and the best available backup path is determined according to the comprehensive priority evaluation coefficient of each available backup path; Step 4: Select the best available alternative route and provide it to the control panel in the logistics vehicle, and display it to guide the logistics vehicle driver to drive along the best available alternative route.

[0007] As a further solution of the present invention: in the step 1, the process of optimizing the logistics path by using the high-precision map system is to model the logistics network as a weighted graph, generate a path set by a graph search algorithm, select a set of feasible alternative paths that meet the constraints according to the total path length, total path time and environmental friendliness, and sort them by a preset priority function, and finally select the optimal set of feasible alternative paths in the specific manner of; AS1: Use high-precision map system to obtain all road segment information in the logistics network; AS2: Logistics Network via Weighted Graph It indicates that, is a collection of nodes; is a set of edges, representing the road connections in the logistics network. Each edge , represents a path from one node to another; and each edge The properties include: length , driving time , Carbon emissions , fuel consumption ; AS3: Enumerate all from arrive The feasible path of : ; AS4: Every feasible path is a set of ordered edges , in, n, A feasible path The road in the middle; its global properties are: Total path length: ; Total path time: ; Total fuel consumption for the route: ; Total carbon emissions by path: ; AS5: Setting path generation constraints from a set of feasible paths Determine the set of alternate paths that can be taken; Total path length constraint: ; in, , Departure point and destination Straight-line distance; It is the tolerance for detours; Filter the set of alternate paths that meet the conditions: ; Total path time constraint: ; in, It is expressed as the maximum allowed time for a customer's order; Filter the set of alternate paths that meet the conditions: ; Next, perform environmentally friendly constraints: ; in, is the environmental friendliness coefficient, and is the weight coefficient; Filter the set of alternate paths that meet the conditions: ; in, is the maximum allowable environmental cost; AS6: Next, to generate the final set of viable backup paths, the comprehensive priority function is determined by the following formula: : ; in, is the priority coefficient; Finally, determine the set of alternate paths that can be taken, and press Sort from small to large, take the first The paths are used as the final set of available backup paths. : ; in, is the default value.

[0008] As a further solution of the present invention: in the step 2, the total cost includes load balancing cost, road use adaptability cost and logistics vehicle long-term cost.

[0009] As a further solution of the present invention: the specific method of obtaining the optimal set of available alternative paths and determining the total cost of each available alternative path in the set of available alternative paths in the transportation of logistics vehicles is: BS1: High-load operation of logistics vehicles will increase energy consumption and loss, and load balancing costs Determined by the following formula: ; in, is the set of available alternative paths Any one of can take the backup path, and , is the maximum load capacity of the logistics vehicle, Represented as current load; Represented as a path The slope weight of BS2: Road use adaptation costs Determined by the following formula: ; in, Indicates that an alternate path can be taken Frequency of use, Indicates the usage frequency of the available alternative path that is most frequently used among the available alternative paths; BS3: Long-term costs of logistics vehicles Determined by the following formula: ; in, Indicates that an alternate path can be taken Impact on logistics vehicle maintenance costs, Indicates that an alternate path can be taken The impact on fuel economy.

[0010] As a further solution of the present invention: Indicates that an alternate path can be taken Impact on logistics vehicle maintenance costs, Indicates that an alternate path can be taken The specific method for determining the degree of impact on fuel economy is as follows: Logistics vehicle maintenance cost Determined by the following formula: ; in, Represented as a road The slope size, is the weight factor; Represented as a road The quality of road conditions; is the weight factor; Economic impact Determined by the following formula: ; in, Indicates that the logistics vehicle can take an alternative route The total time required, load The instantaneous fuel consumption function of the logistics vehicle is: It is a function of time t, indicating the instantaneous speed of the logistics vehicle at a certain moment.

[0011] As a further solution of the present invention: in the step 3, according to the total cost of each available standby path in the available standby path set, a comprehensive priority evaluation is performed on each available standby path to obtain a comprehensive priority evaluation coefficient of each available standby path, and the specific method of determining the best available standby path according to the comprehensive priority evaluation coefficient of each available standby path is: The alternative path can be determined by the following formula The comprehensive priority evaluation coefficient , ; in: is the weight factor; Then calculate each available alternative path in the available alternative path set The comprehensive priority evaluation coefficient ,according to Sort from small to large and select the alternate path with the smallest comprehensive priority evaluation coefficient. As the best alternative path : .

[0012] A logistics path scheduling system for logistics vehicles, comprising: The path generation and screening module is used to determine the departure and destination of the logistics vehicle, optimize the logistics path process using a high-precision map system, model the logistics network as a weighted graph, generate a path set through a graph search algorithm, screen the set of available alternative paths that meet the constraints based on the total path length, total path time, and environmental friendliness, and sort them using a preset priority function to ultimately select the optimal set of available alternative paths; The path cost evaluation module is used to obtain the optimal set of available alternative paths and determine the total cost of each available alternative path in the set of available alternative paths for logistics vehicle transportation; A comprehensive priority evaluation module is used to perform a comprehensive priority evaluation on each available backup path according to the total cost of each available backup path in the available backup path set, obtain a comprehensive priority evaluation coefficient of each available backup path, and determine the best available backup path according to the comprehensive priority evaluation coefficient of each available backup path; The route publishing and guidance module is used to select the best available alternative route and provide it to the control panel in the logistics vehicle, and display it to guide the logistics vehicle driver to drive along the best available alternative route.

[0013] The present invention provides a logistics path scheduling method and system for logistics vehicles. Compared with the prior art, it has the following beneficial effects: The present invention uses a high-precision map system and a graph search algorithm to accurately calculate and screen the carbon emissions and energy consumption of a route, and directly uses environmental friendliness as a key constraint for route selection. The present invention explicitly introduces carbon emissions and fuel consumption as route evaluation indicators, and sets an environmental friendliness coefficient to ensure that the selected route can minimize carbon emissions. Secondly, the present invention establishes a comprehensive cost evaluation model with multiple dimensions including load balancing, road condition adaptability, and long-term vehicle costs. By accurately calculating the energy loss under different paths, the energy consumption of logistics vehicles can be effectively reduced; and it can scientifically quantify and optimize energy utilization efficiency, thereby reducing energy waste at the source and achieving the goal of energy conservation and emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below in conjunction with the accompanying drawings.

[0015] Figure 1 A flow chart of the steps of a logistics path scheduling method for logistics vehicles of the present invention; Figure 2 This is a structural framework diagram of a logistics path scheduling system for logistics vehicles of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1 See also Figure 1 ,The present invention provides a logistics path scheduling method for logistics vehicles, comprising: Step 1: Determine the departure and destination of the logistics vehicle, use the high-precision map system to optimize the logistics path process, model the logistics network as a weighted graph, generate a path set through a graph search algorithm, select a set of alternate paths that meet the constraints based on the total path length, total path time, and environmental friendliness, and sort them through a preset priority function to finally select the optimal set of alternate paths; The process of optimizing the logistics path by using the high-precision map system is to model the logistics network as a weighted graph, generate a path set by a graph search algorithm, select a set of feasible alternative paths that meet the constraints according to the total path length, total path time and environmental friendliness, and sort them by a preset priority function, and finally select the optimal set of feasible alternative paths in the following specific manner; AS1: Use high-precision mapping systems (such as GPS or GIS databases) to obtain information about all road sections in the logistics network, including: section length, road type (highway, urban road, rural road, etc.), speed limit, slope and other characteristics; AS2: Logistics Network via Weighted Graph It indicates that, is a collection of nodes (places in the logistics network, including the departure point and destination ); is a set of edges, representing the road connections in the logistics network. Each edge , represents the road from one node to another; that is, e represents the road from the starting point To destination A specific section of a path is the basic unit of the path; and each edge The properties include: length , driving time , Carbon emissions , fuel consumption ; AS3: Enumerate all the shortest paths from arrive The feasible path of , that is, all the departure points To destination The set of feasible paths It is a weighted graph The starting point is The end point is A collection of paths: ; AS4: Every feasible path is a set of ordered edges ,in, n, A feasible path The road in the middle; its global properties are: Total path length: ; Total path time: ; Total fuel consumption for the route: ; Total carbon emissions by path: ; AS5: Setting path generation constraints from a set of feasible paths Determine the set of alternate paths that can be taken; Total path length constraint: ; in, , Departure point and destination Straight-line distance; is the detour tolerance (e.g. Allow The specific detour will be set by professional staff; Filter the set of alternate paths that meet the conditions: ; Total path time constraint: ; in, It indicates the maximum allowed time for customer orders, and the specific time will be determined by professional staff; Filter the set of alternate paths that meet the conditions: ; Next, perform environmentally friendly constraints: ; in, is the environmental friendliness coefficient, and is the weight coefficient; Filter the set of alternate paths that meet the conditions: ; in, It is the maximum allowable environmental cost, which is set by professional staff; AS6: Next, to generate the final set of viable backup paths, the comprehensive priority function is determined by the following formula: : ; in, It is the priority coefficient, which reflects the emphasis in a specific scenario and is adjusted according to actual needs; Finally, determine the set of alternate paths that can be taken, and press Sort from small to large, take the first The paths are used as the final set of alternate paths. : ; in, It is a preset value, which will be determined by professional staff; With the support of high-precision map systems, this step realizes intelligent and precise optimization of logistics routes by constructing weighted graph models and graph search algorithms. It not only considers traditional route length and time, but also introduces environmental friendliness dimensions. Through comprehensive evaluation of dynamic factors, it can generate a multi-dimensional, multi-constrained feasible route set. This method can not only significantly improve the scientific nature of route selection, but also effectively reduce carbon emissions and energy consumption while ensuring transportation efficiency. Step 2: Obtain the optimal set of available alternative paths and determine the total cost of each available alternative path in the set of available alternative paths for logistics vehicle transportation; The total cost includes load balancing cost, road use adaptability cost and logistics vehicle long-term cost; The specific method of obtaining the optimal set of available alternative paths and determining the total cost of each available alternative path in the set of available alternative paths in the transportation of logistics vehicles is as follows: BS1: High-load operation of logistics vehicles will increase energy consumption and loss, and load balancing costs Determined by the following formula: ; in, is the set of available alternative paths Any one of can take the backup path, and , is the maximum load capacity of the logistics vehicle, Represents the current load; Represented as a path The slope weight (the additional load cost per unit slope); BS2: Road use adaptation costs Determined by the following formula: ; in, Indicates that an alternate path can be taken The usage frequency is the sum of the number of times each section of the route is used. It is determined by professional staff based on the historical transportation routes of logistics vehicles. The larger the value, the more crowded the route. Indicates the usage frequency of the available alternative path that is most frequently used among the available alternative paths; BS3: Long-term costs of logistics vehicles Determined by the following formula: ; in, Indicates that an alternate path can be taken Impact on logistics vehicle maintenance costs, Indicates that an alternate path can be taken the extent of the impact on fuel economy; Logistics vehicle maintenance cost Determined by the following formula: ; in, Represented as a road The specific parameters of the slope are set by professional staff according to the road section information. is the weight factor, which is expressed as the weight of the slope on the maintenance cost of the logistics vehicle; Represented as a road The road condition quality, the specific parameters are set by professional staff according to the road section information; is the weight factor, which indicates the weight of road conditions on the maintenance cost of logistics vehicles; Economic impact Determined by the following formula: ; in, Indicates that the logistics vehicle can take an alternative route The total time required, load The instantaneous fuel consumption function of the logistics vehicle is: It is a function of time t, indicating the instantaneous speed of the logistics vehicle at a certain moment; This step constructs a comprehensive logistics path cost evaluation system from three dimensions: load balancing, road use adaptability, and long-term vehicle costs. The mathematical model accurately calculates the energy consumption of vehicles under different loads and road conditions, and considers the impact of slope and road quality on vehicle maintenance, so as to scientifically quantify the comprehensive economic efficiency of each alternative path. This multi-dimensional and dynamic cost evaluation method can not only help logistics companies reduce operating costs, but also extend the service life of vehicles, and achieve the coordinated optimization of economic and environmental benefits. Step 3: According to the total cost of each available backup path in the available backup path set, a comprehensive priority evaluation is performed on each available backup path to obtain a comprehensive priority evaluation coefficient of each available backup path, and the best available backup path is determined according to the comprehensive priority evaluation coefficient of each available backup path; According to the total cost of each available standby path in the available standby path set, a comprehensive priority evaluation is performed on each available standby path to obtain a comprehensive priority evaluation coefficient of each available standby path, and a specific method of determining the best available standby path according to the comprehensive priority evaluation coefficient of each available standby path is as follows: The alternative path can be determined by the following formula The comprehensive priority evaluation coefficient , ; in: is the weight factor, which is determined by professional staff; Then calculate each available alternative path in the available alternative path set The comprehensive priority evaluation coefficient ,according to Sort from small to large and select the alternate path with the smallest comprehensive priority evaluation coefficient. As the best alternative path : ; Step 4: Select the best available alternative route and provide it to the control panel in the logistics vehicle, and display it to guide the logistics vehicle driver to drive along the best available alternative route.

[0018] Embodiment 2 See also Figure 2 In the specific implementation process, this embodiment is based on the first embodiment and is different from the first embodiment in that this embodiment further provides a logistics path scheduling system for logistics vehicles, including: The path generation and screening module is used to determine the departure and destination of the logistics vehicle, optimize the logistics path process using a high-precision map system, model the logistics network as a weighted graph, generate a path set through a graph search algorithm, screen the set of available alternative paths that meet the constraints based on the total path length, total path time, and environmental friendliness, and sort them using a preset priority function to ultimately select the optimal set of available alternative paths; The path cost evaluation module is used to obtain the optimal set of available alternative paths and determine the total cost of each available alternative path in the set of available alternative paths for logistics vehicle transportation; A comprehensive priority evaluation module is used to perform a comprehensive priority evaluation on each available backup path according to the total cost of each available backup path in the available backup path set, obtain a comprehensive priority evaluation coefficient of each available backup path, and determine the best available backup path according to the comprehensive priority evaluation coefficient of each available backup path; The route publishing and guidance module is used to select the best available alternative route and provide it to the control panel in the logistics vehicle, and display it to guide the logistics vehicle driver to drive along the best available alternative route.

[0019] Embodiment 3 The specific implementation process of this embodiment includes the entire implementation process of the above two groups of embodiments.

[0020] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0021] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A logistics path scheduling method for logistics vehicles, characterized in that: include: Step 1: Determine the departure and destination of the logistics vehicle, use the high-precision map system to optimize the logistics path process, model the logistics network as a weighted graph, generate a path set through a graph search algorithm, select a set of alternate paths that meet the constraints based on the total path length, total path time, and environmental friendliness, and sort them through a preset priority function to finally select the optimal set of alternate paths; Step 2: Obtain the optimal set of available alternative paths and determine the total cost of each available alternative path in the set of available alternative paths for logistics vehicle transportation; Step 3: According to the total cost of each available backup path in the available backup path set, a comprehensive priority evaluation is performed on each available backup path to obtain a comprehensive priority evaluation coefficient of each available backup path, and the best available backup path is determined according to the comprehensive priority evaluation coefficient of each available backup path; Step 4: Select the best available alternative route and provide it to the control panel in the logistics vehicle, and display it to guide the logistics vehicle driver to drive along the best available alternative route.

2. A logistics path scheduling method for logistics vehicles according to claim 1, characterized in that: In step 1, the process of optimizing the logistics path by using the high-precision map system is to model the logistics network as a weighted graph, generate a path set by a graph search algorithm, select a set of alternate paths that meet the constraints according to the total path length, total path time and environmental friendliness, and sort them by a preset priority function. The specific method of finally selecting the optimal set of alternate paths is as follows: AS1: Use high-precision map system to obtain all road segment information in the logistics network; AS2: Logistics Network via Weighted Graph It indicates that, is a collection of nodes; is a set of edges, representing the road connections in the logistics network. Each edge , represents a path from one node to another; and each edge The properties include: length , driving time , Carbon emissions , fuel consumption ; AS3: Enumerate all from via graph search algorithm arrive The feasible path of : ； AS4: Every feasible path is a set of ordered edges ,in, n, A feasible path The road in the middle; its global properties are: Total path length: ; Total path time: ; Total fuel consumption for the route: ; Total carbon emissions by path: ; AS5: Setting path generation constraints from a set of feasible paths Determine the set of alternate paths that can be taken; Total path length constraint: ; in, , Departure point and destination Straight-line distance; It is the tolerance for detours; Filter the set of alternate paths that meet the conditions: ; Total path time constraint: in, It is expressed as the maximum allowed time for a customer's order; Filter the set of alternate paths that meet the conditions: ; Next, perform environmentally friendly constraints: ; in, is the environmental friendliness coefficient, and is the weight coefficient; Filter the set of alternate paths that meet the conditions: ; in, is the maximum allowable environmental cost; AS6: Next, to generate the final set of viable backup paths, the comprehensive priority function is determined by the following formula: : ； in, is the priority coefficient; Finally, determine the set of alternate paths that can be taken, and press Sort from small to large, take the first The paths are used as the final set of available backup paths. : ； in, is the default value.

3. The method for logistics path scheduling of logistics vehicles according to claim 1, characterized in that: In the step 2, the total cost includes load balancing cost, road use adaptability cost and logistics vehicle long-term cost.

4. A logistics path scheduling method for logistics vehicles according to claim 3, characterized in that: The specific method of obtaining the optimal set of available alternative paths and determining the total cost of each available alternative path in the set of available alternative paths in the transportation of logistics vehicles is as follows: BS1: High-load operation of logistics vehicles will increase energy consumption and loss, and load balancing costs Determined by the following formula: ; in, is the set of available alternative paths Any one of can take the backup path, and , is the maximum load capacity of the logistics vehicle, Represented as current load; Represented as a path The slope weight of BS2: Road use adaptation costs Determined by the following formula: ； in, Indicates that an alternate path can be taken Frequency of use, Indicates the usage frequency of the available alternative path that is most frequently used among the available alternative paths; BS3: Long-term costs of logistics vehicles Determined by the following formula: ； in, Indicates that an alternate path can be taken Impact on logistics vehicle maintenance costs, Indicates that an alternate path can be taken The impact on fuel economy.

5. A logistics path scheduling method for logistics vehicles according to claim 4, characterized in that: Said Indicates that an alternate path can be taken Impact on logistics vehicle maintenance costs, Indicates that an alternate path can be taken The specific method for determining the degree of impact on fuel economy is as follows: Logistics vehicle maintenance cost Determined by the following formula: ； in, Represented as a road The slope size, is the weight factor; Represented as a road The quality of road conditions; is the weight factor; Economic impact Determined by the following formula: ; in, Indicates that the logistics vehicle can take an alternative route The total time required, load The instantaneous fuel consumption function of the logistics vehicle is: It is a function of time t, indicating the instantaneous speed of the logistics vehicle at a certain moment.

6. A logistics path scheduling method for logistics vehicles according to claim 5, characterized in that: In the step 3, according to the total cost of each available standby path in the available standby path set, a comprehensive priority evaluation is performed on each available standby path to obtain a comprehensive priority evaluation coefficient of each available standby path. The specific method of determining the best available standby path according to the comprehensive priority evaluation coefficient of each available standby path is as follows: The alternative path can be determined by the following formula The comprehensive priority evaluation coefficient , ； in: is the weight factor; Then calculate each available alternative path in the available alternative path set The comprehensive priority evaluation coefficient ,according to Sort from small to large and select the alternate path with the smallest comprehensive priority evaluation coefficient. As the best alternative path : .

7. A logistics path scheduling system for logistics vehicles, applied to a logistics path scheduling method for logistics vehicles according to any one of claims 1 to 6, characterized in that: include: The path generation and screening module is used to determine the departure and destination of the logistics vehicle, optimize the logistics path process using a high-precision map system, model the logistics network as a weighted graph, generate a path set through a graph search algorithm, screen the set of available alternative paths that meet the constraints based on the total path length, total path time, and environmental friendliness, and sort them using a preset priority function to ultimately select the optimal set of available alternative paths; The path cost evaluation module is used to obtain the optimal set of available alternative paths and determine the total cost of each available alternative path in the set of available alternative paths for logistics vehicle transportation; A comprehensive priority evaluation module is used to perform a comprehensive priority evaluation on each available backup path according to the total cost of each available backup path in the available backup path set, obtain a comprehensive priority evaluation coefficient of each available backup path, and determine the best available backup path according to the comprehensive priority evaluation coefficient of each available backup path; The route publishing and guidance module is used to select the best available alternative route and provide it to the control panel in the logistics vehicle, and display it to guide the logistics vehicle driver to drive along the best available alternative route.

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