CN113962639A - Distribution path planning method and system based on global map - Google Patents
Distribution path planning method and system based on global map Download PDFInfo
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Abstract
The invention relates to the technical field of logistics distribution, in particular to a distribution path planning method and system based on a global map. The method comprises the following steps: grid loading global map data to generate a road network vector map; acquiring the coordinates of the distribution center and the respective geographic positions of the lifting points, and matching the coordinates to a road network vector map; expanding the distribution center to the periphery until the distribution center is met, and dividing the distribution center into distribution subarea areas; acquiring attributes of orders to be distributed, dividing distribution centers for the orders, and marking position coordinates of the individual distribution orders; taking the distribution central position as an initial coordinate point, taking the respective lifting point and the independent distribution order position as node coordinates, and calculating the carrying capacity cost of each linear raster road passing through the node coordinates; and calculating the optimal path of all nodes passing by under the condition of the maximum cargo capacity of the distributed vehicles in the road network vector map based on a Dijkstra algorithm. The invention improves the work efficiency of dispatching the parts of each distribution center in the global map.
Description
Technical Field
The invention relates to the technical field of logistics distribution, in particular to a distribution path planning method and system based on a global map.
Background
With the rapid development of electronic commerce, the amount of orders is increasing, and the logistics distribution matched with the orders faces huge challenges and new opportunities. In order to better serve customers and improve the timeliness of logistics distribution, the reasonable arrangement of logistics distribution paths becomes the key for improving distribution efficiency, reducing distribution cost and shortening distribution time. At present, the problem of unreasonable order distribution and irregular delivery path exist in the logistics order delivery process, when a large number of orders are faced, the delivery center delivers the orders in a sorting and scribing area according to the knowledge and experience of the local environment, so that the orders are delivered frequently and repeatedly, a large amount of delivery time is delayed, and the logistics delivery efficiency is reduced.
Disclosure of Invention
The embodiment of the invention aims to provide a distribution path planning method and system based on a global map, aiming at the problems that distribution efficiency is reduced and distribution paths cannot be optimized due to unreasonable arrangement of logistics distribution paths.
In order to achieve the above purpose, the embodiment of the present invention provides the following technical solutions:
in a first aspect, in an embodiment provided by the present invention, a method for planning a distribution route based on a global map is provided, including:
loading global map data, and rasterizing the global map data to generate a road network vector map;
acquiring the coordinates of the distribution center and the respective geographic positions of the lifting points, and matching the coordinates to a road network vector map;
expanding the distribution centers to the periphery until the distribution centers meet with each other by taking the distribution centers as expansion sources, and dividing the distribution centers into distribution subareas on the road network vector map;
acquiring attributes of orders to be distributed, clustering the orders, dividing distribution centers according to corresponding distribution subarea areas, and marking position coordinates of the single distribution orders in a road network vector map according to the attributes of the orders;
taking the distribution center position as an initial coordinate point, taking the respective lifting point and the independent distribution order position as node coordinates, and calculating the carrying capacity cost of the passing node coordinates of each linear raster road in the road network vector map;
and calculating the optimal path of all nodes passing by under the condition of the maximum cargo capacity of the distributed vehicles in the road network vector map based on a Dijkstra algorithm.
In some embodiments of the present invention, the rasterizing the global map data to generate the road network vector map includes:
acquiring global map data, and reading road network vector data based on the global map data;
planning a road network according to the road network vector data to obtain a road network planning result;
subdividing a road network planning result into a continuously distributed linear grid road scene model;
performing vector expansion on the linear raster roads of the scene model, and determining the maximum distribution coverage range of the adjacent linear raster roads;
and overlapping the linear grid road scene model after vector expansion in a space vector field of the global map to establish and generate a road network vector map.
In some embodiments provided by the invention, the global map data comprises loaded map data and road network vector data, and when road network planning is performed on the road network vector data, the method further comprises the step of removing roads to be avoided, wherein the roads to be avoided are logistics distribution vehicle forbidden road sections, traffic accidents and traffic control road sections and environmental factor driving slow road sections, and the environmental factor driving slow road sections comprise congested road sections obtained through real-time networking based on the global map data.
In some embodiments provided herein, the method of determining maximum delivery coverage of adjacent linear grid roads includes:
traversing the linear grid road of the acquired scene model;
calculating the maximum distance value between adjacent linear grid roads in the scene model;
setting a threshold value of the linear grid road vector expansion in a numerical range from the maximum distance value to half of the maximum distance value;
and generating the maximum distribution coverage range on the linear grid road by taking the threshold value as a vector expansion standard.
In some embodiments provided by the present invention, the method for partitioning the distribution partition area includes:
acquiring the geographic position coordinates of a distribution center, and matching the coordinates to a road network vector map;
expanding the coordinates of the geographic position of the distribution center to the periphery until the coordinates meet each other by taking the coordinates of the geographic position of the distribution center as an expansion source to form a Voronoi diagram in the road network vector map space;
and determining the Voronoi image area where each distribution center is positioned as a divided distribution subarea area.
In some embodiments provided by the invention, when a Voronoi diagram is constructed, two adjacent distribution center geographical position coordinates are used as two extension sources, a vertical bisector connecting two extension source line segments is drawn, and the vertical bisectors drawn by taking all distribution centers in the global map as the extension sources are combined to form a distribution subarea area formed by continuous polygons in the global map.
In some embodiments provided by the present invention, the to-be-delivered order attributes include an address of the to-be-delivered order, an order weight, a package volume, a self-service point pick-up permission condition, and an order delivery time limit.
In some embodiments provided by the present invention, a method for clustering orders includes:
according to the obtained attributes of the orders to be distributed, distributing the orders to the corresponding distribution subarea areas according to the positions corresponding to the addresses of the orders to be distributed;
distributing the allowed collection order to the self-picking point with the shortest distance according to the self-picking point collection permission condition of the attribute of the order to be distributed, and changing the position coordinate of the allowed collection order in the road network vector map to the self-picking point position;
marking position coordinates of the individual delivery orders in the road network vector map for the orders signed by the unlicensed agent;
and matching the corresponding linear grid roads according to the maximum delivery coverage range of the self-pickup position and the single delivery order position.
In some embodiments, the marked location of the pick-up point and the location of the individual delivery order in the road network vector map correspond to a linear grid road to which at least one order can be delivered.
In some embodiments provided by the present invention, the method for calculating the load capacity cost of each linear raster road passing through the node coordinate includes:
counting the number of coordinates of the passing nodes of each linear raster road and order attribute information of each node;
calculating the order weight and the package volume of each node on the linear raster road according to the order attribute information;
accumulating the order weight and the wrapping volume of all the nodes on the linear raster road;
and defining the sum of the order weight and the sum of the package volume as the carrying capacity cost of the coordinates of the passing node of the linear raster road.
In some embodiments provided by the present invention, a method for calculating an optimal path passing through all nodes in a road network vector map based on Dijkstra algorithm includes:
taking the coordinates of a distribution center in the road network vector map as coordinates of a starting point;
selecting the basis by taking the maximum cargo capacity of the distribution vehicle as the number of nodes passing by;
and on the premise of meeting the maximum cargo capacity of the distribution vehicles, expanding outwards layer by taking the coordinates of the starting point of the distribution center as the center until all the nodes to be distributed correspond to a linear grid road and the distribution vehicles, and obtaining the optimal path of all the nodes passing by in the road network vector map.
In some embodiments of the present invention, the maximum cargo capacity of the delivery vehicle is the total of the order weight or the total of the package volume that satisfies the loading requirement of the delivery vehicle first.
In a second aspect, in another embodiment provided by the present invention, a distribution path planning system based on a global map is provided, where the distribution path planning system based on the global map obtains optimal paths for all orders by using the distribution path planning method based on the global map; the global map-based distribution path planning system comprises:
the road network vector map generation module is used for carrying out grid processing on the basis of the loaded global map data to obtain a road network vector map;
the order dividing module is used for dividing the order into distribution centers of corresponding distribution subarea areas according to the order attributes;
the load capacity cost calculation module is used for calculating the required load capacity of the order corresponding to the passing node of each linear raster road;
and the distribution path generation module is used for calculating the optimal path of all nodes passing through under the condition of the maximum cargo capacity of the distribution vehicle in the road network vector map based on the Dijkstra algorithm.
The technical scheme provided by the invention has the following beneficial effects:
according to the global map-based distribution path planning method and system, the global map data is fully utilized to predict the order distribution range, the distribution transportation quantity, the distribution receiving place and the distribution path, and the distribution scheme which meets the requirements of distribution of all orders, the maximum cargo capacity of the distribution vehicle and the optimization of the distribution path is obtained through comprehensive calculation according to the position of the distribution center. Powerful support provided by the global map data for distribution path planning is fully utilized, logistics order distribution is more refined, and the work efficiency of dispatching pieces of each distribution center in the global map is improved.
These and other aspects of the invention are apparent from and will be elucidated with reference to the embodiments described hereinafter. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or technical solutions in the related art, the drawings, which are needed to be used in the description of the exemplary embodiments or related art, will be briefly described below, and are used for providing further understanding of the present invention and are a part of the specification, and together with the embodiments of the present invention, serve to explain the present invention without limiting the present invention. In the drawings:
fig. 1 is a flowchart of a distribution route planning method based on a global map according to an embodiment of the present invention.
Fig. 2 is a flowchart of generating a road network vector map in the global map-based distribution route planning method according to the embodiment of the present invention.
Fig. 3 is a flowchart of determining a maximum distribution coverage area in a distribution path planning method based on a global map according to an embodiment of the present invention.
Fig. 4 is a flowchart of dividing distribution partition areas in a distribution path planning method based on a global map according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of two-by-two connection of extension sources on a road network vector map in a distribution path planning method based on a global map according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of dividing distribution partition areas by drawing perpendicular bisectors between extended sources in the distribution path planning method based on the global map according to the embodiment of the present invention.
Fig. 7 is a flowchart illustrating order clustering performed in a distribution path planning method based on a global map according to an embodiment of the present invention.
Fig. 8 is a flowchart of calculating a load capacity cost in the distribution path planning method based on the global map according to the embodiment of the present invention.
Fig. 9 is a flowchart of calculating an optimal path in a distribution path planning method based on a global map according to an embodiment of the present invention.
Fig. 10 is a system block diagram of a global map-based distribution route planning system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In some of the flows described in the present specification and claims and in the above figures, a number of operations are included that occur in a particular order, but it should be clearly understood that these operations may be performed out of order or in parallel as they occur herein, with the order of the operations being indicated as 101, 102, etc. merely to distinguish between the various operations, and the order of the operations by themselves does not represent any order of performance. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.
The technical solutions in the exemplary embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the exemplary embodiments of the present invention, and it is apparent that the described exemplary embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, the problem of unreasonable order distribution and irregular delivery path exist in logistics order delivery, when a large number of orders are faced, the delivery center performs sorting and zone delivery according to the knowledge and experience of the local environment, so that the orders are delivered frequently and repeatedly, a large amount of delivery time is delayed, and the logistics delivery efficiency is reduced.
In order to solve the above problems, embodiments of the present invention provide a method and a system for planning a distribution route based on a global map.
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings.
Example 1
Referring to fig. 1, fig. 1 is a flowchart of a distribution route planning method based on a global map according to the present invention. One embodiment of the invention provides a distribution path planning method based on a global map, which comprises the following steps:
s1: and loading the global map data, and rasterizing the global map data to generate the road network vector map.
In this embodiment, the global map data is a high-precision map including all distribution areas of the city to be distributed, and has the functions of high positioning precision and real-time data updating, and road-level navigation information is provided according to the high positioning precision. And performing grid processing on the loaded global map data to generate a road network vector map for the next distribution path planning.
Specifically, referring to fig. 2, the step S1 of rasterizing the global map data to generate the road network vector map includes the following steps:
s101, acquiring global map data, and reading road network vector data based on the global map data;
s102, planning a road network according to the road network vector data to obtain a road network planning result;
s103, segmenting a road network planning result into a continuously distributed linear grid road scene model;
s104, performing vector expansion on the linear raster roads of the scene model, and determining the maximum distribution coverage range of the adjacent linear raster roads;
and S105, overlapping the linear grid road scene model after vector expansion in a space vector field of the global map, and establishing and generating the road network vector map.
In this embodiment, the global map data includes loaded map data and road network vector data. The loaded global high-precision map data may be read from the loaded global map data, including road network vector data. And planning the road network according to the read road network vector data. And the method also comprises the step of removing roads to be avoided.
Specifically, the road to be avoided is a road section where logistics distribution vehicles are prohibited from driving, a traffic accident and traffic control road section, and a road section where environmental factors are retarded in driving. The road section with the environmental factor driving delay comprises a congested road section caused by external environmental factors such as commuting or high peak periods, rain and snow, water accumulation, dense fog or municipal road maintenance, and the congested road section is obtained in a real-time networking mode based on global map data.
When the distribution route is generated, the road needing to be avoided can be automatically avoided.
And segmenting a continuously distributed linear raster road scene model according to a road network planning result, and expanding the linear raster road in a way of setting the road coverage width when performing vector expansion on the linear raster road. For example, a range of 50 meters on each side of the linear grid road is set as a vector expansion space, and the maximum distribution coverage of the linear grid road is obtained.
In this embodiment, referring to fig. 3, the method of determining the maximum delivery coverage of adjacent linear grid roads includes the steps of:
s1041, traversing the linear grid road of the acquired scene model;
s1042, calculating the maximum distance value between adjacent linear grid roads in the scene model;
s1043, setting a threshold value of the linear grid road vector expansion in a numerical range from the maximum distance value to half of the maximum distance value;
and S1044, generating the maximum distribution coverage range on the linear grid road by taking the threshold value as a vector expansion standard.
In particular, the maximum distance value is a value at which two roads are separated by the maximum distance in the entire linear-grid road scene model, and the set threshold value is at least half of the maximum distance value, so that when the linear-grid road is loaded on any one linear-grid road of the scene model, the maximum distribution coverage area formed by the linear-grid road can be covered at any position of the global map, and the maximum distribution coverage area of the linear-grid road cannot be covered.
Namely: any region of the global map is located in the maximum distribution coverage range of at least one linear grid road, and any region to be distributed has the linear grid road to reach.
S2: and acquiring the distribution center and the respective lifting point geographical position coordinates, and matching the distribution center and the respective lifting point geographical position coordinates to the road network vector map.
In particular, the distribution center position and the respective destination geographical positions of the area where the global map is located are known data, and the road network vector map is marked by marking the distribution center and the respective destination positioning positions.
S3: and expanding the distribution centers to the periphery until the distribution centers meet the distribution centers, and dividing the distribution centers into distribution subareas on the road network vector map.
As described above, in step S2, the distribution centers are marked, and it is necessary to divide distribution partition areas for each distribution center in the constructed road network vector map in order to dispatch the order package to each pick-up point or customer sign-in point using the distribution center as a transfer station.
In this embodiment, referring to fig. 4, a method for constructing a Voronoi graph to express, specifically, to divide a distribution partition area includes the following steps:
s301, acquiring the geographic position coordinates of a distribution center, and matching the geographic position coordinates to a road network vector map;
s302, expanding the coordinates of the geographic position of the distribution center to the periphery until the coordinates meet each other by taking the coordinates of the geographic position of the distribution center as an expansion source to form a Voronoi diagram in a road network vector map space;
and S303, determining the Voronoi image area where each distribution center is located as a divided distribution subarea area.
Referring to fig. 5, when the distribution subarea is divided, the adjacent extension sources on the road network vector map are connected in pairs according to the geographical position coordinates of the distribution centers marked on the road network vector map in step S2 as the extension sources, as shown in fig. 6, a vertical bisector connecting two extension source line segments is drawn, and the vertical bisectors drawn by using all the distribution centers in the global map as the extension sources are combined to form the distribution subarea area composed of continuous polygons in the global map.
By the distribution partition area division method, all areas of the global map can be divided into different distribution centers for administration, including respective points located in different distribution partition areas.
S4: obtaining attributes of orders to be distributed, clustering the orders, dividing distribution centers according to corresponding distribution subarea areas, and marking position coordinates of the single distribution orders in a road network vector map according to the attributes of the orders.
In this embodiment, the attributes of the order to be delivered include an address of the order to be delivered, an order weight, a package volume, a permission condition for the pick-up point to sign up, and an order delivery time limit.
Referring to fig. 7, when an order to be delivered is divided into corresponding delivery centers by clustering, the method for clustering the order includes:
s401, according to the obtained attributes of the orders to be distributed, distributing the orders to corresponding distribution subarea areas according to the positions corresponding to the addresses of the orders to be distributed;
s402, distributing the allowed collection order to the self-picking point with the shortest distance according to the self-picking point collection permission condition of the order attribute to be distributed, and changing the position coordinate of the allowed collection order in the road network vector map to the self-picking point position;
s403, marking position coordinates of the single distribution orders in the road network vector map for the orders which are not allowed to sign in;
and S404, matching the corresponding linear grid road according to the self-picking point position and the maximum distribution coverage range of the single distribution order position.
Firstly, address information of an order to be distributed in the attribute of the order to be distributed is read, a distribution subarea area to which the order belongs is marked in a road network vector map according to the address information of the order to be distributed, a distribution center corresponding to the order to be distributed is inquired, and the order package is sent to each distribution center.
Then, according to the self-pick-up point collection permission condition of the attribute of the order to be distributed, the order is divided to the self-pick-up point with the nearest distance or the position needing distribution is directly marked in the road network vector map. And matches the corresponding deliverable linear grid road.
As can be seen from the maximum distribution coverage generated in step S104, all regions of the global map are located within the coverage of at least one linear grid road. Therefore, the self-picking point position and the single delivery order position marked in the road network vector map correspond to the linear grid road to which at least one order can be sent.
S5: and calculating the carrying capacity cost of the coordinates of the nodes of each linear raster road in the road network vector map by taking the distribution central position as an initial coordinate point and taking the respective lifting point and the independent distribution order position as the coordinates of the nodes.
In this embodiment, referring to fig. 8, the calculation of the capacity cost includes the following steps:
s501, counting the number of coordinates of passing nodes of each linear grid road and order attribute information of each node;
s502, calculating the order weight and the package volume of each node on the linear raster road according to the order attribute information;
s503, accumulating the order weights and the wrapping volumes of all the nodes on the linear raster road;
s504, defining the sum of the order weight and the sum of the package volume as the carrying capacity cost of the coordinates of the passing node of the linear raster road.
When the coordinates of the passing nodes of each linear raster road are counted, the distribution center of the distribution subarea area where the linear raster road is located is used as the center of a circle, the linear raster roads distributed in the radial direction are used as lines, and the coordinates of the passing nodes are connected in series. In order to avoid repeated crossing of linear raster roads, at least 12 distributable linear raster roads can be formed in the road network vector map by taking the distribution center as the center of a circle and taking a fixed included angle as a constraint for distributing the linear raster roads, for example, taking a fixed included angle of 30 degrees as an example; and connecting the respective lifting points in the distribution subarea area covered by the fixed included angle and the nodes of the independent distribution order positions in series to generate at least one linear grid road.
And selecting a linear grid road with the shortest distribution time as the preferred path of the area in the area with the fixed included angle.
And calculating the total order weight and the total parcel volume of all the nodes on the linear raster road, wherein the total order weight and the total parcel volume are the carrying capacity cost on the linear raster road and are used for measuring the order volume on the linear raster road.
S6: and calculating the optimal path of all nodes passing by under the condition of the maximum cargo capacity of the distributed vehicles in the road network vector map based on a Dijkstra algorithm.
In this embodiment, referring to fig. 9, a method for calculating an optimal path includes:
s601, taking the coordinates of a distribution center in a road network vector map as coordinates of a starting point;
s602, selecting the basis by taking the maximum cargo capacity of a distribution vehicle as the number of nodes passing by;
and S603, expanding outwards layer by taking the initial point coordinate of the distribution center as the center on the premise of meeting the maximum cargo capacity of the distribution vehicle until all the nodes to be distributed correspond to a linear grid road and the distribution vehicle, and obtaining the optimal path of all the nodes passing by in the road network vector map.
The maximum cargo capacity of the delivery vehicle is the order cargo capacity which firstly meets the loading requirement of the delivery vehicle and is the sum of the order weight or the sum of the package volume.
On the premise that the maximum loading capacity of the vehicle is known, the delivery vehicle firstly selects the delivery to take the delivery center as a starting point, orders of all nodes from near to far are distributed until one of the sum of the weight of the orders or the sum of the volume of packages in the carrying capacity cost corresponding to the nodes capable of being distributed reaches the loading capacity of the delivery vehicle, and the linear raster road from the delivery center to the selected nodes is an optimal path.
Orders corresponding to the remaining nodes in the area where the linear grid road fails to reach the fixed included angle are automatically distributed to the distribution vehicles corresponding to the adjacent linear grid roads, and the distribution vehicles corresponding to the adjacent linear grid roads are used for filling the carrying capacity.
And when the distribution vehicles corresponding to the adjacent linear grid roads cannot be loaded, distributing all the rest nodes in the distribution subarea area where the distribution center is located by adding at least one emergency vehicle.
Or when the order arrival time limit of the remaining nodes is sufficient, the nodes to be distributed of the next round of the distribution vehicle of the linear grid road or the adjacent linear grid road are counted.
The invention relates to a global map-based distribution path planning method, which is characterized in that a road network vector map is used as a basis for distribution path planning, distribution subareas are divided in a global map range for all orders, all orders are wrapped and distributed to corresponding distribution centers, order sign-in positions of the distribution subarea areas are processed in a coordinate node marking mode, and optimal paths passing through all nodes under the condition of maximum cargo capacity of distribution vehicles are calculated based on a Dijkstra algorithm. The purpose of rapidly distributing all order packages is met, and a distribution scheme which meets the requirements of dispatching of distribution vehicles, the maximum cargo capacity of the distribution vehicles and the optimization of distribution paths is obtained.
It should be understood that although the steps are described above in a certain order, the steps are not necessarily performed in the order described. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, some steps of the present embodiment may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or in turns with other steps or at least a part of the steps or stages in other steps.
Example 2
Referring to fig. 10, an embodiment of the present invention provides a distribution route planning system based on a global map, including a road network vector map generating module 100, an order dividing module 200, a capacity cost calculating module 300, and a distribution route generating module 400. Wherein:
the road network vector map generation module 100 performs a rasterization process based on the loaded global map data to obtain a road network vector map.
In this embodiment, the road network vector map generation module 100 obtains global map data by means of loaded map data and road network vector data, rasterizes the global map data, plans a road network according to the read road network vector data to obtain a road network planning result, divides the road network planning result into continuously distributed linear raster road scene models, vector-expands the linear raster roads of the scene models, determines the maximum distribution coverage range of adjacent linear raster roads, superimposes the vector-expanded linear raster road scene models in a space vector field of the global map, and creates and generates a road network vector map.
The constructed road network vector map covers any position of the global map, any region of the global map is located in the maximum distribution coverage range of at least one linear raster road, and any region to be distributed has the linear raster road to reach.
The order dividing module 200 is configured to divide the order into distribution centers of corresponding distribution partition areas according to the order attributes.
In this embodiment, before order division, a distribution partition area corresponding to a distribution center needs to be divided in a road network vector map, and the specific steps are as follows: acquiring the geographic position coordinates of a distribution center, and matching the coordinates to a road network vector map; the geographic position coordinates of the distribution center are used as an expansion source to expand towards the periphery until meeting, and a Voronoi diagram in the road network vector map space is formed; and determining the Voronoi image area where each distribution center is positioned as a divided distribution subarea area.
And when the order is divided, acquiring the attribute of the order to be distributed, clustering the order, dividing a distribution center according to the corresponding distribution subarea area, and marking the position coordinate of the single distribution order in the road network vector map according to the attribute of the order.
The attributes of the orders to be delivered comprise the addresses of the orders to be delivered, the weights of the orders, the package volumes, the permission conditions of the self-service points to pick up the orders and the delivery time limit of the orders.
When the orders to be distributed are divided into the corresponding distribution centers through clustering, the process of clustering the orders mainly comprises the following steps: according to the obtained attributes of the orders to be distributed, distributing the orders to the corresponding distribution subarea areas according to the positions corresponding to the addresses of the orders to be distributed; distributing the allowed collection order to the self-picking point with the shortest distance according to the self-picking point collection permission condition of the attribute of the order to be distributed, and changing the position coordinate of the allowed collection order in the road network vector map to the self-picking point position; marking position coordinates of the individual delivery orders in the road network vector map for the orders signed by the unlicensed agent; and matching the corresponding linear grid roads according to the maximum delivery coverage range of the self-pickup position and the single delivery order position.
The carrying capacity cost calculating module 300 is configured to calculate a required carrying capacity of an order corresponding to a passing node of each linear raster road.
In this embodiment, the method for calculating the capacity cost by the capacity cost calculation module 300 is as follows: counting the number of coordinates of the passing nodes of each linear raster road and order attribute information of each node; calculating the order weight and the package volume of each node on the linear raster road according to the order attribute information; accumulating the order weight and the wrapping volume of all the nodes on the linear raster road; and defining the sum of the order weight and the sum of the package volume as the carrying capacity cost of the coordinates of the passing node of the linear raster road.
And calculating the total order weight and the total parcel volume of all the nodes on the linear raster road, wherein the total order weight and the total parcel volume are the carrying capacity cost on the linear raster road and are used for measuring the order volume on the linear raster road.
The distribution route generating module 400 calculates an optimal route passing through all nodes under the condition of the maximum cargo capacity of the distribution vehicle in the road network vector map based on Dijkstra algorithm.
In this embodiment, the process of the distribution route generating module 400 calculating the optimal route is as follows: taking the coordinates of a distribution center in the road network vector map as coordinates of a starting point; selecting the basis by taking the maximum cargo capacity of the distribution vehicle as the number of nodes passing by; and on the premise of meeting the maximum cargo capacity of the distribution vehicles, expanding outwards layer by taking the coordinates of the starting point of the distribution center as the center until all the nodes to be distributed correspond to a linear grid road and the distribution vehicles, and obtaining the optimal path of all the nodes passing by in the road network vector map.
In this embodiment, the global map-based distribution route planning system is implemented by adopting the steps of the global map-based distribution route planning method according to the foregoing embodiments. Therefore, the operation process of the global map-based distribution route planning system in this embodiment will not be described in detail.
In summary, the global map-based distribution path planning method and system provided by the invention make full use of global map data to predict order distribution range, distribution traffic volume, distribution receiving location and distribution path, and comprehensively calculate to obtain a distribution scheme meeting the optimization of distribution vehicle scheduling, distribution vehicle maximum cargo capacity and distribution path of all order distribution by combining the position of the distribution center. Powerful support provided by the global map data for distribution path planning is fully utilized, logistics order distribution is more refined, and the work efficiency of dispatching pieces of each distribution center in the global map is improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A distribution path planning method based on a global map is characterized by comprising the following steps:
loading global map data, and rasterizing the global map data to generate a road network vector map;
acquiring the coordinates of the distribution center and the respective geographic positions of the lifting points, and matching the coordinates to a road network vector map;
expanding the distribution centers to the periphery until the distribution centers meet with each other by taking the distribution centers as expansion sources, and dividing the distribution centers into distribution subareas on the road network vector map;
acquiring attributes of orders to be distributed, clustering the orders, dividing distribution centers according to corresponding distribution subarea areas, and marking position coordinates of the single distribution orders in a road network vector map according to the attributes of the orders;
taking the distribution center position as an initial coordinate point, taking the respective lifting point and the independent distribution order position as node coordinates, and calculating the carrying capacity cost of the passing node coordinates of each linear raster road in the road network vector map;
and calculating the optimal path of all nodes passing by under the condition of the maximum cargo capacity of the distributed vehicles in the road network vector map based on a Dijkstra algorithm.
2. The global map-based distribution route planning method according to claim 1, wherein the rasterizing global map data to generate a road network vector map comprises:
acquiring global map data, and reading road network vector data based on the global map data;
planning a road network according to the road network vector data to obtain a road network planning result;
subdividing a road network planning result into a continuously distributed linear grid road scene model;
performing vector expansion on the linear raster roads of the scene model, and determining the maximum distribution coverage range of the adjacent linear raster roads;
and overlapping the linear grid road scene model after vector expansion in a space vector field of the global map to establish and generate a road network vector map.
3. The global map-based distribution route planning method according to claim 2, wherein the method of determining the maximum distribution coverage of the adjacent linear grid roads comprises:
traversing the linear grid road of the acquired scene model;
calculating the maximum distance value between adjacent linear grid roads in the scene model;
setting a threshold value of the linear grid road vector expansion in a numerical range from the maximum distance value to half of the maximum distance value;
and generating the maximum distribution coverage range on the linear grid road by taking the threshold value as a vector expansion standard.
4. The global map-based distribution route planning method according to claim 1, wherein the method for dividing the distribution partition area comprises:
acquiring the geographic position coordinates of a distribution center, and matching the coordinates to a road network vector map;
expanding the coordinates of the geographic position of the distribution center to the periphery until the coordinates meet each other by taking the coordinates of the geographic position of the distribution center as an expansion source to form a Voronoi diagram in the road network vector map space;
and determining the Voronoi image area where each distribution center is positioned as a divided distribution subarea area.
5. The method for planning a distribution route based on a global map as claimed in claim 4, wherein when the Voronoi map is constructed, the coordinates of the geographic positions of two adjacent distribution centers are used as two extended sources, vertical bisectors connecting two extended source line segments are drawn, and the vertical bisectors drawn by using all the distribution centers in the global map as the extended sources are combined to form a distribution subarea area composed of continuous polygons in the global map.
6. The global map-based distribution path planning method according to claim 3, wherein the to-be-distributed order attributes include an address of the to-be-distributed order, an order weight, a package volume, a free pick-up point pick-up permission condition, and an order arrival time limit.
7. The global map-based distribution route planning method according to claim 6, wherein the method of clustering orders comprises:
according to the obtained attributes of the orders to be distributed, distributing the orders to the corresponding distribution subarea areas according to the positions corresponding to the addresses of the orders to be distributed;
distributing the allowed collection order to the self-picking point with the shortest distance according to the self-picking point collection permission condition of the attribute of the order to be distributed, and changing the position coordinate of the allowed collection order in the road network vector map to the self-picking point position;
marking position coordinates of the individual delivery orders in the road network vector map for the orders signed by the unlicensed agent;
and matching the corresponding linear grid roads according to the maximum delivery coverage range of the self-pickup position and the single delivery order position.
8. The method for planning a distribution route based on a global map according to claim 7, wherein the calculation method of the load capacity cost of the coordinates of the route nodes of each linear raster road comprises:
counting the number of coordinates of the passing nodes of each linear raster road and order attribute information of each node;
calculating the order weight and the package volume of each node on the linear raster road according to the order attribute information;
accumulating the order weight and the wrapping volume of all the nodes on the linear raster road;
and defining the sum of the order weight and the sum of the package volume as the carrying capacity cost of the coordinates of the passing node of the linear raster road.
9. The method for planning a distribution route based on a global map as claimed in claim 8, wherein the method for calculating the optimal route passing through all nodes in the road network vector map based on Dijkstra algorithm comprises:
taking the coordinates of a distribution center in the road network vector map as coordinates of a starting point;
selecting the basis by taking the maximum cargo capacity of the distribution vehicle as the number of nodes passing by;
and on the premise of meeting the maximum cargo capacity of the distribution vehicles, expanding outwards layer by taking the coordinates of the starting point of the distribution center as the center until all the nodes to be distributed correspond to a linear grid road and the distribution vehicles, and obtaining the optimal path of all the nodes passing by in the road network vector map.
10. A global map-based distribution path planning system, which is characterized in that the global map-based distribution path planning system obtains the optimal paths for distribution of all orders by adopting the global map-based distribution path planning method of any one of claims 1 to 9; the global map-based distribution path planning system comprises:
the road network vector map generation module is used for carrying out grid processing on the basis of the loaded global map data to obtain a road network vector map;
the order dividing module is used for dividing the order into distribution centers of corresponding distribution subarea areas according to the order attributes;
the load capacity cost calculation module is used for calculating the required load capacity of the order corresponding to the passing node of each linear raster road; and
and the distribution path generation module is used for calculating the optimal path of all nodes passing through under the condition of the maximum cargo capacity of the distribution vehicle in the road network vector map based on the Dijkstra algorithm.
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